Utilizing credit and informatic data for insurance underwriting purposes

ABSTRACT

Systems and methods include one or more dwelling sensors configured to generate sensor data representative of characteristics of a dwelling; a telematics device configured to generate telematics data representative of operational characteristics of a vehicle; and an analysis server. The analysis server receives the sensor data; receives the telematics data; receives credit information regarding an insured; and determines one or more insurance policy decisions based upon the sensor data, the telematics data, and the credit information the one or more insurance policy decisions comprising: a premium amount, a deductible amount, a coverage amount, a coverage term, or any combination there of for the insured.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. patent application Ser. No.15/365,773, filed on Nov. 30, 2016, which claims priority to Ser. No.14/305,732, filed Jun. 16, 2014, which claims priority to: 61/866,779filed Aug. 16, 2013; 61/926,093 filed Jan. 10, 2014; 61/926,091 filedJan. 10, 2014; 61/926,095 filed Jan. 10, 2014; 61/926,098 filed Jan. 10,2014; 61/926,103 filed Jan. 10, 2014; 61/926,108 filed Jan. 10, 2014;61/926,111 filed Jan. 10, 2014; 61/926,114 filed Jan. 10, 2014;61/926,118 filed Jan. 10, 2014; 61/926,119 filed Jan. 10, 2014;61/926,121 filed Jan. 10, 2014; 61/926,123 filed Jan. 10, 2014;61/926,536 filed Jan. 13, 2014; 61/926,541 filed Jan. 13, 2014;61/926,534 filed Jan. 13, 2014; 61/926,532 filed Jan. 13, 2014;61/943,897 filed Feb. 24, 2014; 61/943,901 filed Feb. 24, 2014;61/943,906 filed Feb. 24, 2014; and 61/948,192 filed Mar. 5, 2014, eachof which are incorporated herein by reference in their entirety.

FIELD OF THE INVENTION

The disclosed embodiments generally relate to a method and computerizedsystem for managing insurance and related products and services, andmore particularly, to using data captured from an insured property fordetermining underwriting, pricing, and other insurance relateddecisions.

BACKGROUND OF THE INVENTION

Smart home functionality is a maturing space, but the opportunity forinsurance companies remains largely untapped. Currently, there are fewuseful early warning and loss mitigation systems that actually savecosts and time for both the property owner and insurance company alike.For instance, currently, homeowners insurance claim events are detectedby the homeowner, who contacts the insurance company to inform them thatthere has been a loss. However, the loss could be mitigated withautomated warning and detection systems that interface with theinsurance company systems. For example, homeowners may not become awareof minor to medium hail damage to their roofs until such time as thatdamage leads to water damage to the interior or exterior of the home. Ifthey could be made aware of such loss events earlier and then takecorrective actions, then the increased damage could have been mitigatedor avoided.

Another maturing space concerns vehicle telematics in which the latestdevelopments in automotive electronics are dealing with the automaticmonitoring of the state of a vehicle. Such monitoring is based on theintegration of numerous sensors into the vehicle such that importantfunctional parts and components may be monitored. It is becoming ofincreasing interest to collect a variety of information, regardingdifferent aspects of a vehicle, which may have different applicationsdepending on their usage. The use of telematics in automobiles hasbecome more common in recent years, particularly as implemented within-car navigation systems.

Finally, another maturing area relates to the use of credit information,such as a credit score or credit history, in making underwriting,pricing or other decisions about the terms and conditions on which tooffer or provide insurance coverage. Such use involves modeling andmaking determinations as to whether there is a correlation between aperson's credit information and the person's risk profile (which mayaffects the person's insurance rates).

In this regard, there is utility and functionality to be provided byutilizing smart home and vehicle telematics data with creditinformation, as factors in formulating the terms of an insurance policyto be issued or offered.

SUMMARY OF THE INVENTION

The purpose and advantages of the below described illustratedembodiments will be set forth in and apparent from the description thatfollows. Additional advantages of the illustrated embodiments will berealized and attained by the devices, systems and methods particularlypointed out in the written description and claims hereof, as well asfrom the appended drawings.

To achieve these and other advantages and in accordance with the purposeof the illustrated embodiments, in one aspect, a computer device andmethod for processing risk or loss related data to determine insuranceunderwriting, pricing, or other decisions contingent upon informatic andcredit score data is provided. An insurance underwriting decision isidentified which is to be rendered regarding an insured. Informatic datais received from one or more of an insured property and vehicleassociated with the insured. Credit score data relating to the insuredis also received. Analytics is performed on the received informatic dataand credit score data to determine the insurance underwriting, pricing,or other decision.

In another aspect, numerous sensors may be installed in a vehicle inorder to measure and/or record a variety of information, regardingdifferent aspects of the vehicle. For example, the sensors may recordinformation such as movements, status and behavior of a vehicle, or anyother factors. The information captured by the vehicle telematics may beutilized, for example, to ensure that the premiums policyholders arepaying are reflective of their driving style and the way their vehicleis used. In another aspect, a determination is made as to whether thereceived credit score data is to be utilized to determine the insuranceunderwriting, pricing, or other decision. In yet another aspect, aweighted value for the received credit score data is determined to beutilized to determine the insurance underwriting, pricing, or otherdecision.

This summary section is provided to introduce a selection of concepts ina simplified form that are further described subsequently in thedetailed description section. This summary section is not intended toidentify key features or essential features of the claimed subjectmatter, nor is it intended to be used to limit the scope of the claimedsubject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying appendices and/or drawings illustrate variousnon-limiting, example, inventive aspects in accordance with the presentdisclosure:

FIG. 1 illustrates an example system for acquiring and transmittingvarious types of data in a smart house environment, in accordance withembodiments presented herein;

FIG. 2 illustrates a network computer device/node, in accordance withembodiments presented herein;

FIG. 3 is a flow diagram of a method for acquiring structuralinformatics using the system of FIG. 1 , in accordance with embodimentspresented herein;

FIG. 4 is a flow diagram of a method for adjusting insurance policy databased on information acquired using the system of FIG. 1 , in accordancewith embodiments presented herein;

FIG. 5 is a flow diagram of a method for adjusting insurance policy databased on information acquired using the system of FIG. 1 , in accordancewith embodiments presented herein;

FIG. 6 is a flow diagram of a method for making additional adjustmentsto an insurance policy data based on information acquired using thesystem of FIG. 1 , in accordance with embodiments presented herein;

FIG. 7 is a flow diagram of a method for generating a warranty based oninformation acquired using the system of FIG. 1 , in accordance withembodiments presented herein;

FIG. 8 is a flow diagram of a method for scheduling repairs based oninformation acquired using the system of FIG. 1 , in accordance withembodiments presented herein;

FIG. 9 is a flow diagram of a method for determining a value of astructure based on information acquired using the system of FIG. 1 , inaccordance with embodiments presented herein;

FIG. 10 is a flow diagram of a method for adjusting insurance termsbased on information acquired using the system of FIG. 1 , in accordancewith embodiments presented herein;

FIG. 11 is a schematic block diagram of an example communication networkillustratively comprising nodes/devices (e.g., sensors, client computingdevices, routers/switches, smart phone devices, servers, and the like)interconnected by various methods of communication, in accordance withembodiments presented herein;

FIG. 12A is a schematic block diagram of an example network-computingdevice 2030 (e.g., one of network devices) that may be used (orcomponents thereof), in accordance with embodiments presented herein;

FIG. 12B is a block diagram illustrating a device of FIG. 12A, inaccordance with embodiments presented herein;

FIG. 13 is a block diagram illustrating dwelling-computing devicecoupled to various below described sensor types, in accordance withembodiments presented herein;

FIG. 14 is a block diagram illustrating server 2012 receiving data, thedata being used in various ways, in accordance with embodimentspresented herein;

FIG. 15 is a flow chart, illustrating a process in which data may berecorded and used, in accordance with embodiments presented herein;

FIG. 16 is a flow chart, illustrating a process where dwelling analyzercollects data from sensors, in accordance with embodiments presentedherein;

FIG. 17 is a flow diagram of a process of operational steps of theappliance analyzer module of FIG. 13 , in accordance with embodimentspresented herein;

FIG. 18 is a flowchart, illustrating a process where dwelling analyzerpreferably collects data from sensors to determine a number of peopleoccupying the dwelling at various points in time for insurance purposes,in accordance with embodiments presented herein;

FIG. 19 is a flow diagram of a process of operational steps of thepolicy analyzer module of FIG. 13 , in accordance with embodimentspresented herein;

FIG. 20 is a flowchart illustrating a process where dwelling analyzerpreferably collects data from sensors, in accordance with embodimentspresented herein;

FIG. 21 is a flow diagram of a process of operational steps of thepolicy analyzer module of FIG. 13 , in accordance with embodimentspresented herein;

FIG. 22 is a flow diagram of operational steps of the policy analyzermodule of FIG. 13 in accordance with embodiments presented herein;

FIG. 23 is a flow chart, illustrating operational steps of an applianceanalyzer, in accordance with embodiments presented herein;

FIGS. 24 and 25 are flow charts, illustrating operational steps of adwelling analyzer, in accordance with embodiments presented herein;

FIG. 26 is a process, illustrating dwelling analyzer collecting datafrom sensors, in accordance with embodiments presented herein;

FIG. 27 is a flowchart, illustrating operational steps of themaintenance manager module of FIG. 13 , in accordance with embodimentspresented herein;

FIG. 28 is block diagram, illustrating an insurance server coupled to acomputing device for receiving data from sensors, in accordance withembodiments presented herein;

FIG. 29 is a flowchart, illustrating operational steps of the dataanalyzer, in accordance with embodiments presented herein;

FIG. 30 is a flowchart, illustrating a process where data analyzerpreferably collects data related to a policyholder's dwelling fromsensors placed at various locations in and around the dwelling, inaccordance with embodiments presented herein;

FIG. 31 is a flowchart, illustrating a process where dwelling analyzerpreferably collects data from sensors to determine a number of peopleoccupying the dwelling at various points in time for insurance purposes,in accordance with embodiments presented herein;

FIG. 32 is a flowchart, illustrating operational steps of the policyanalyzer module of FIG. 13 , in accordance with embodiments presentedherein;

FIG. 33 is a block diagram, illustrating an insurance server coupled tocomputing device for receiving data from sensors preferably relating toa dwelling, in accordance with embodiments presented herein;

FIG. 34 is a flowchart, illustrating operational steps of the policymanager, in accordance with embodiments presented herein;

FIG. 35 is a schematic diagram, illustrating an electronic device thatis displaying a graphical-user-interface (GUI), in accordance withembodiments presented herein;

FIG. 36A is a schematic diagram, illustrating a graphical user interfacepresentation, in accordance with embodiments presented herein; and

FIG. 36B is a schematic diagram, illustrating a plan view of a roof, inaccordance with embodiments presented herein.

DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS

The illustrated embodiments are now described more fully with referenceto the accompanying drawings wherein like reference numerals identifysimilar structural/functional features. The illustrated embodiments arenot limited in any way to what is illustrated as the illustratedembodiments described below are merely exemplary, which can be embodiedin various forms as appreciated by one skilled in the art. Therefore, itis to be understood that any structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representation for teaching one skilled in the artto variously employ the discussed embodiments. Furthermore, the termsand phrases used herein are not intended to be limiting but rather toprovide an understandable description of the illustrated embodiments.Also, the flow charts and methods described herein do not imply eitherrequired steps or a required order to the steps, and the illustratedembodiments and processes may be implemented in any order and/orcombination that is practicable.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this the embodiments described herein belongs. Althoughany methods and materials similar or equivalent to those describedherein can also be used in the practice or testing of the illustratedembodiments, exemplary methods and materials are now described.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an,” and “the” include plural referents unless thecontext clearly dictates otherwise. Thus, for example, reference to “astimulus” includes a plurality of such stimuli and reference to “thesignal” includes reference to one or more signals and equivalentsthereof known to those skilled in the art, and so forth.

It is to be appreciated the illustrated embodiments discussed below arepreferably a software algorithm, program or code residing on computeruseable medium having control logic for enabling execution on a machinehaving a computer processor. The machine typically includes memorystorage configured to provide output from execution of the computeralgorithm or program.

As used herein, the term “software” is meant to be synonymous with anycode or program that can be in a processor of a host computer,regardless of whether the implementation is in hardware, firmware or asa software computer product available on a disc, a memory storagedevice, or for download from a remote machine. The embodiments describedherein include such software to implement the equations, relationshipsand algorithms described above. One skilled in the art will appreciatefurther features and advantages of the illustrated embodiments based onthe above-described embodiments. Accordingly, the illustratedembodiments are not to be limited by what has been particularly shownand described, except as indicated by the appended claims. Commonlyassigned U.S. Pat. Nos. 8,289,160 and 8,400,299 are related to certainembodiments described herein and are each incorporated herein byreference in their entirety.

As used herein, the term “insurance” refers to a contract between aninsurer, known as an insurance company, and an insured, also known as apolicy holder, in which compensation is paid by the insurer to theinsured for some specific losses in exchange of a certain premium amountperiodically paid by the insured in past. In a typical usage, wheneverthe insured suffers some loss for which he/she has insured or holdspolicy, the insured may file an insurance claim to request compensationfor the loss.

As also used herein, “insured” may refer to an applicant for a newinsurance policy and/or may refer to an insured of an existing insurancepolicy.

As used herein, the term “insurance policy” may encompass a warranty orother contract for the repair, service, or maintenance of insuredproperty.

As used herein, “dwelling” or “insured property” means a dwelling, otherbuildings or structures, personal property, or business property, aswell as the premises on which these are located, some or all which maybe covered by an insurance policy.

As used herein, “decision”, when referenced regarding an insurancepolicy, means a decision to modify an insurance policy's terms orconditions if permitted by the terms of the policy, a decision tocondition renewal or continuation of the policy on certainmodifications, a decision to terminate or cancel the insurance policy,and/or a decision to offer or recommend modifications to the policy'sterms or conditions that the insured may accept or reject.

As used herein, “underwriting decisions” encompasses pricing decisionsfor an insurance policy.

Turning now descriptively to the drawings, FIG. 1 depicts an exemplarysystem 100 communicatively connected to sensors or one or more imagingdevices (e.g., camera devices) relative to a dwelling in which belowillustrated embodiments may be implemented. As to be further describedbelow, it is to be understood examples of sensors and imaging devicesinclude, but are not limited to, camera devices, webcams, smarttelevision camera devices (and other appliance camera devices), smartphone devices, tablet devices, satellite imaging devices (includinghigh-device imaging satellite devices), infrared and/or radar devicesand the like. It is to be further understood that first and secondnetworks 50 are each a geographically-distributed collection of nodesinterconnected by communication links and segments for transporting databetween end nodes, such as personal computers, work stations, smartphone devices, tablets, televisions, sensors and or other devices suchas automobiles, etc. Many types of networks are available, with thetypes ranging from local area networks (LANs) to wide area networks(WANs). LANs typically connect the nodes over dedicated privatecommunications links located in the same general physical location, suchas a dwelling, structure, residence or campus. WANs, on the other hand,typically connect geographically dispersed nodes over long-distancecommunications links, such as common carrier telephone lines, opticallight paths, synchronous optical networks (SONET), synchronous digitalhierarchy (SDH) links, or Powerline Communications (PLC), and others.

Communications 75 represents computerized communications as known bythose skilled in the art. For instance, communications 75 may be wiredlinks or may comprise a wireless communication medium, where certainnodes are in communication with other nodes, e.g., based on distance,signal strength, current operational status, location, etc. Moreover,each of the devices can communicate data packets (or frames) with otherdevices using predefined network communication protocols as will beappreciated by those skilled in the art, such as various wired protocolsand wireless protocols etc., where appropriate. In this context, aprotocol consists of a set of rules defining how the nodes interact witheach other. Those skilled in the art will understand that any number ofnodes, devices, links, etc. may be used in the computer network, andthat the view shown herein is for simplicity. Also, while theembodiments are shown herein with reference to a general network cloud,the description herein is not so limited, and may be applied to networksthat are hardwired.

As will be appreciated by one skilled in the art, aspects of thepresently disclosed embodiments may be a system, method or computerprogram product. Accordingly, aspects of the presently disclosedembodiments may take the form of an entirely hardware embodiment, anentirely software embodiment (including firmware, resident software,micro-code, etc.) or an embodiment combining software and hardwareaspects that may generally be referred to herein as a “circuit,”“module” or “system.” Furthermore, aspects of the presently disclosedembodiments may take the form of a computer program product embodied inone or more computer readable medium(s) having computer readable programcode embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Forexemplary purposes and without limitations, examples of the computerreadable storage medium include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer-readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresently disclosed embodiments may be written in any combination of oneor more programming languages, including an object-oriented programminglanguage such as Java, Smalltalk, C++ or the like and conventionalprocedural programming languages, such as the “C” programming languageor similar programming languages. The program code may execute entirelyon the server computer, partly on the server computer, as a stand-alonesoftware package, partly on the server computer and partly on a remotecomputer (such as dwelling computing device 300) or entirely on theremote computer. In the latter scenario, the remote computer may beconnected to the server computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), a combinationthereof, or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider).

Aspects of the presently disclosed embodiments are described below withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems) and computer program products according toembodiments of the present disclosure. It will be understood that eachblock of the flowchart illustrations and/or block diagrams, andcombinations of blocks in the flowchart illustrations and/or blockdiagrams, can be implemented by computer program instructions. Thesecomputer program instructions may be provided to a processor of ageneral-purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

These computer program instructions may also be stored in anon-transitory computer readable medium that can direct a computer,other programmable data processing apparatus, or other devices tofunction in a particular manner, such that the instructions stored inthe computer readable medium produce an article of manufacture includinginstructions which implement the function/act specified in the flowchartand/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions that execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

Turning to FIG. 1 , system 100 includes sensors 90, cameras 92, andmanagement module 105 that includes retrieval engine 110, data engine120, command generation engine 130, policy engine 140, and warrantyengine 142. In one embodiment, first network 50 is a LAN and secondnetwork 50 is a WAN (best shown in FIG. 1 ), such as the Internet,although it is contemplated herein that networks 50 may be any systemand/or method of computerized communications as understood by thoseskilled in the art.

FIG. 2 is a schematic block diagram of an example computing device 300that may be used (or components thereof) with one or more embodimentsdescribed herein. As explained above, in different embodiments thesevarious devices may be configured to communicate with each other in anysuitable way, such as, for example, via communication 75 over networks50.

Device 300 is one example of a suitable system and is not intended tosuggest any limitation as to the scope of use or functionality ofembodiments described herein. Regardless, computing device 300 iscapable of being implemented and/or performing any of the functionalityset forth herein.

Computing device 300 is operational with numerous other general purposeor special purpose computing system environments or configurations.Examples of well-known computing systems, environments, and/orconfigurations that may be suitable for use with computing device 300include, but are not limited to, personal computer systems, servercomputer systems, thin clients, thick clients, hand-held or laptopdevices, multiprocessor systems, microprocessor-based systems, set topboxes, programmable consumer electronics, network PCs, minicomputersystems, mainframe computer systems, and distributed data processingenvironments that include any of the above systems or devices, and thelike.

Computing device 300 may be described in the general context of computersystem-executable instructions, such as program modules, being executedby a computer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.Computing device 300 may be practiced in distributed data processingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed dataprocessing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

Device 300 is shown in FIG. 2 in the form of a general-purpose computingdevice. The components of device 300 may include, but are not limitedto, one or more processors or processing units 310, a system memory 340,interface device 320, and a bus 305 that couples various systemcomponents including system memory 340 to processor 310.

Bus 305 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnect (PCI) bus.

Computing device 300 typically includes a variety of computer systemreadable media. Such media may be any available media that is accessibleby device 300, and it includes both volatile and non-volatile media,removable and non-removable media.

System memory 340 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 342, cachememory, and hard drive 345, which may include database 346. Computingdevice 300 may further include other removable/non-removable,volatile/non-volatile computer system storage media. By way of exampleonly, hard drive 345 can be provided for reading from and writing to anon-removable, non-volatile magnetic media. Interface device 320includes, without limitation, a magnetic disk drive for reading from andwriting to a removable, non-volatile magnetic disk (e.g., a “floppydisk”), and an optical disk drive for reading from or writing to aremovable, non-volatile optical disk such as a CD-ROM, DVD-ROM or otheroptical media can be provided. In such instances, each can be connectedto bus 305 by one or more data media interfaces. As will be furtherdepicted and described below, memory 340 may include at least oneprogram product having a set (e.g., at least one) of program modulesthat are configured to carry out the functions of embodiments of thepresently disclosed techniques.

Management module 105, has a set (at least one) of engines, such asretrieval engine 110, data engine 120, command generation engine 130,policy engine 140, and warranty engine 142 described below, which may bestored in memory 340, and may function solely or in combination with anoperating system, one or more application programs, other programmodules, and program data. Each of the operating system, one or moreapplication programs, other program modules, and program data or somecombination thereof, may include an implementation of a networkingenvironment. Management module 105 may generally carry out the functionsand/or methodologies of embodiments of the disclosure as describedherein.

Device 300 may also communicate with one or more interface devices 320such as a keyboard, a pointing device, a display, etc.; one or moredevices that enable a user to interact with computing device 300; and/orany devices (e.g., network card, modem, etc.) that enable computingdevice 300 to communicate with one or more other computing devices. Suchcommunication can occur via Input/Output (I/O) interfaces. Still yet,device 300 can communicate with one or more networks such as a localarea network (LAN), a general wide area network (WAN), and/or a publicnetwork (e.g., the Internet) via a network adapter 320. As depicted,network adapter 320 communicates with the other components of computingdevice 300 via bus 305. It should be understood that, although notshown, other hardware and/or software components could be used inconjunction with device 300. Examples, include, but are not limited to:microcode, device drivers, redundant processing units, external diskdrive arrays, RAID systems, tape drives, and data archival storagesystems, etc.

FIGS. 1 and 2 are intended to provide a brief, general description of anillustrative and/or suitable exemplary environment in which embodimentsof the below described present disclosure may be implemented. FIGS. 1and 2 are exemplary of a suitable environment and are not intended tosuggest any limitation as to the structure, scope of use, orfunctionality of an embodiment of the present disclosure. A particularenvironment should not be interpreted as having any dependency orrequirement relating to any one or combination of components illustratedin an exemplary operating environment. For example, in certaininstances, one or more elements of an environment may be deemed notnecessary and omitted. In other instances, one or more other elementsmay be deemed necessary and added.

Sensor 90 and camera 92 include captured data related to structures. Itis contemplated herein that structures include any type of dwellingstructure (e.g., residential, commercial, retail, municipal, etc.) inwhich the capture and analysis of sensor data is useful for the reasonsat least described herein. It is further contemplated herein thatsensors 90 and cameras 92 may be installed on property that may or maynot have a structure. In one embodiment, sensors 90 and cameras 92communicate directly with management module 105. However, it iscontemplated herein that sensors 90 and cameras 92 may communicate withcomputing device 300 operating on the same network 50 (best shown inFIG. 1 ). In this embodiment, computing device 300 receives informationfrom sensors 90 and cameras 92 and communicates the information tomanagement module 105. Computing device 300 may immediately transfer theinformation to management module 105, it may be a delayed transfer(e.g., scheduled for the middle of the night when internet usage islow), and/or it may be any communication methodology as known by thoseskilled in the art. Computing device 300 is preferably configured andoperational to receive (capture) data from various sensors 90 andcameras 92 regarding certain measured aspects of the dwelling andtransmit that captured data to a management module 105 via network 50.It is noted that device 300 may perform analytics regarding the capturedsensor or imagery data regarding the dwelling, and/or management module105, preferably located or controlled by an insurance company/carrier,may perform such analytics, as also further described below. Further,sensors 90 and cameras 92 may be connected to computing device 300 bywire, or by a wireless technology, or via any communication methodologyas known by those skilled in the art.

Although various sensor and camera types are illustrated in FIG. 1 anddescribed below, the sensor types described and shown herein are notintended to be exhaustive as embodiments of the present disclosure mayencompass any type of known or unknown sensor type which facilitates thepurposes and objectives of the certain illustrated embodiments describedherein. Exemplary sensor types include (but are not limited to):

Motion sensor—One type of motion sensor 90 detects motion within a rangeof sensor 90. Thus, motion sensor 90 may be placed to detect whenpeople, animals and/or objects move within sensor's 90 field of vision.Another type of sensor 90 may sense motion in the structure to whichsensor 90 is attached. Although structures typically do not move, in theevent of an earthquake, flood, damage to that part of the structure,and/or other devastating event, motion sensor 90 may detect the movementof the structure itself.

Temperature sensor—Temperature sensor 90 detects the temperature of thedesired medium. Thus, temperature sensor 90 may be configured to measurethe temperature of ambient air or of a specific surface (e.g., the wallto which temperature sensor 90 is attached). It is contemplated hereinthat temperature sensor 90 may be placed outside the structure (e.g., onan outside wall and/or the roof), inside the structure (e.g., on aninterior wall, an interior ceiling, an interior floor, a basement, anattic, a kitchen, a bathroom, a bedroom, a workspace, etc.), or at aboundary there between.

Humidity sensor—As with other sensors 90, humidity sensor 90 may beplaced anywhere inside/outside/on the structure as recognized by thoseskilled in the art.

Gas detection sensor—Detects the presence of various gasses. As withother sensors 90, gas detection sensor 90 may be placed anywhereinside/outside/on the structure as recognized by those skilled in theart. For exemplary purposes, only and without limitation, gas detectionsensor may be configured to detect the presence of carbon monoxide (orany other harmful gasses, such as radon), oxygen, and/or methane (or anyother flammable gasses). Further, the readings may be binary (e.g.,either the gas is present or it is not present), or the readings may bequantitative (e.g., the percentage of air the comprises the gas, partsper million of the gas).

Smoke detector sensor—Detects the presence of smoke. As with othersensors 90, smoke detection sensor 90 may be placed anywhereinside/outside/on the structure as recognized by those skilled in theart. The readings of smoke detection sensor may be binary (e.g., eitherthe gas is present or it is not present), or the readings may bequantitative (e.g., the percentage of air the comprises smoke, parts permillion of smoke).

Water pressure sensor—Detects the water pressure at various locationswithin the structure. Water pressure sensors may monitor water relatedconditions, including (but not limited to): the detection of water andwater pressure detection, for instance in the plumbing system in thedwelling 300. With regards to a water pressure sensor, it may have oneor more probes attached to various locations of the dwelling's 300plumbing, and thus device 103 may record the pressure present in theplumbing, and/or any changes in that pressure. For example, plumbingsystems may be designed to withstand a certain amount of pressure, andif the pressure rises above that amount, the plumbing system may be atrisk for leaking, bursting, or other failure. Thus, device 103 mayrecord the water pressure (and water flow) that is present in theplumbing system at various points in time. Water pressure sensors 90 maybe placed anywhere inside or outside the structure and thus may provideinformation related to the stresses being induced upon the structure'splumbing system. This information may be utilized by management moduleto indicate a plumbing system that is operating close to stress limits,and thus, a structure for which water damage may be more likely.

Water flow sensor—Detects the amount of water flowing through selectedpoints in the plumbing system. Water flow sensor 90 may be placedanywhere inside or outside the structure and thus may provideinformation related to the amount of water being routed to thestructure, and more particularly, which parts of the structure arereceiving exactly (or approximately) how much water. It is contemplatedherein that water flow sensors 90 may detect, for exemplary purposesonly and without limitation, hot water in a water heater, hot waterinput pipes, cold water input pipes, and/or output pipes (e.g., pipesremoving utilized water).

Water detection sensor—Detects any amount of water escaping throughselected points throughout the plumbing system. Water detection sensor90 may be placed anywhere inside the structure and thus may provideinformation related to water escaping and accumulating inside thestructure, which parts of the structure have water accumulation and howmuch water. It is contemplated herein that water detection sensors 90may detect, for exemplary purposes only and without limitation, floodwaters entering from exterior to interior of the structure, wateroverflow from sump pump(s), drains or broken pipes and/or sewer/waterback-ups.

Leak detection sensor—configured and operational to preferably monitorthe presence of leaks from gas and water plumbing pipes both inside andoutside the walls of the structure. The leak detection sensor may haveone or more probes attached to various locations of the structure'splumbing and piping, and may record the fact that there is a gas orwater leak. An example of this is that a leak detection sensor can beplaced behind the washing machine. If the hoses that connect the washingmachine to the water line were to break the leak detection sensor wouldknow that there was a water leak and notify the insured and/or theinsurance company. The insured can also give prior authorization to theinsurance company to act on their behalf to correct the water leak. Forinstance, call a plumber to turn off the water at the street when theleak detector activates and the insured does not respond to the leakdetection sensor after a certain period of time. The leak detectionsensors do not need to necessarily be placed around the appliance orpipe that they are intended to check for leaks. For example, an insuredcould place a sensor on the main water line that goes into the dwelling300 and this sensor could know by changes in pressure, temperature, etc.that there is a later or gas leak in the dwelling 300—even if the leakwas inside the walls and not viewable inside the home. An analysis modelcould use the information about how often the leak detection sensoralerts, whether the insured uses leak detection sensor(s), and wherethey are placed in various ways such as rating the home insurance,tracking water pressure, and/or providing advice and guidance, such asrating the home insurance, tracking water pressure, and/or providingadvice and guidance.

Wind speed sensor—Wind speed sensor 90 detects the wind speed at thatlocation and may be placed anywhere inside or outside the structure.

Air pressure sensor—Air pressure sensor 90 may be placed anywhere insideor outside the structure. This information may be analyzed, for example,to determine how quickly and easily the structure equalizes air pressurechanges to the outside ambient air.

Electrical system sensor—Electrical system sensor 90 detects theoperational parameters of the structure's electrical system. Readingsfrom sensor 90 could be used to determine if the voltage is(persistently) too high, too low, or if the voltage frequently dropsand/or spikes. Such conditions may suggest that the dwelling 300 is atrisk for fire. Other types of electrical measurements could be taken,such as readings of current flowing through the electrical system. Stillother types of electrical measurements could be determined include howenergy is used and at what times of day it is used, etc.

Structural sensor—Structural sensor 90 may be configured to detect the(changing) conditions of the structure's elements (e.g., support beams,floors, ceilings, roofs, walls, etc.). Structural readings from one ormore locations inside and/or outside the structure could thus berecorded by sensor 90 and transmitted to management module 105.

Environmental Sensor—Environmental sensor 90 may be configured to detectvarious environmental conditions relating to dwelling 300, such as theair quality present in the structure, the presence ofmold/bacteria/algae/lead paint or any contaminant adverse to humanhealth (whether airborne or attached to a portion of the structure ofthe structure).

Camera Sensor—Camera sensors may be configured to detect variouswavelengths, including without limitation visible light, infrared, andthermal. Moreover, camera sensors may include visible light cameras,infrared cameras, two-dimensional (2D) cameras, three-dimensional (3D)cameras, radar-capable sensors, aerial imagery, thermal images, sensorsthat detect other wavelengths, and/or any combination thereof. It iscontemplated herein that multiple 2D cameras may be used in cooperationand/or conjunction such that the location of detected objects may bedetermined, such as, again for exemplary purposes and withoutlimitation, a common 3D camera configuration (e.g., two 2D cameraslocated a few inches apart horizontally), and a different 3Dconfiguration (e.g., two 2D cameras located a few inches apartvertically, two or more 2D cameras located at different known locationssuch that the location of commonly detected objects can be calculated).

Although various camera types are illustrated in FIG. 1 and describedbelow, the camera types described and shown herein are not intended tobe exhaustive as embodiments of the present disclosure may encompass anytype of known or unknown camera type which facilitates the purposes andobjectives of the certain illustrated embodiments described herein.Exemplary camera types include but are not limited to:

Visible light two-dimensional (2D) camera—Generally speaking, this isthe camera that is commonly used. This type of camera produces a 2Dimage of the visible light received and detected by the camera.

Visible light three-dimensional (3D) camera—In one embodiment, thiscamera comprises a pair of 2D cameras that are capturing approximatelythe same content, but from different perspectives. The two cameras maybe the same vertical distance from the ground and a few inches aparthorizontally, similar to how peoples' eyes are separated. However, it iscontemplated herein that the cameras may have any arrangement,including, without limitation, only vertical differentiation, bothvertical and horizontal differentiation, and/or three or more cameras.It is further contemplated herein two or more cameras may share a commonlens, to the extent that such is practicable.

Infrared camera—Such a camera would record, detect, and communicateimagery of infrared emissions in its field of view. It is contemplatedherein that such a camera may be specially designed to record infraredimagery, it may be a “normal” camera with a special filter designed tofacilitate infrared imagery, it may be a “normal” camera re-equipped todetect infrared imagery, and/or any configuration and/or means forcapturing infrared imagery as known in the art.

Infrared 3D camera—A combination of cameras that detect infraredemissions, that are typically, although not necessarily, operated intandem and/or cooperation. As with visible light 3D cameras, theinfrared 3D cameras may be arranged in any positions as known and/orpracticed by those skilled in the art.

Multi-function camera—This camera, as the name suggests, performs aplurality of functions, such as, for exemplary purposes only and withoutlimitation, a 2D visible light camera and a 2D infrared camera, a singlecamera that captures both visible light and infrared, a camera thatcaptures wavelengths other than infrared and visible light, and/or anycombination thereof.

Aerial imagery camera—This camera is mounted on an airplane, unmannedaerial vehicle (UAV), satellite, or another device that can takepictures of the dwelling from the sky. These cameras can provide aunique perspective of the dwelling that a picture from the groundcannot. The angles the that are taken in this manner can include by arenot limited to nadir (looking straight down at the dwelling) and allsides of the dwelling.

Camera images from Smartphone or other smart device—this camera cancapture metadata about the direction, GPS coordinate and other dataelements about the picture. The pictures can be taken by the insured, bythe insurance company or a 3rd party company.

Thermal imagery camera—It is contemplated herein that imagery capturedby cameras 92 includes, for exemplary purposes only and withoutlimitation, still picture cameras, video cameras, filtered cameras(e.g., only certain wavelengths, such as visible light green, visiblelight red, certain wavelengths of non-visible light), and/orcombinations thereof.

It is contemplated herein that sensors may collect informatics relatedto the property at which they are located, structure(s) thereon, objectstherein, such as appliances. With respect to objects, it is contemplatedherein that objects may include appliances, vehicles, and/or anything towhich warranty coverage may be applicable. Exemplary appliances include,for exemplary purposes only without limitation, washing machine, dryer,dishwasher, oven, stove, air conditioning, fans, water heater, heater,vacuum system, coffee machine, microwave, toaster oven, (de)humidifier,refrigerator, clothing iron, radiator, sewing machine.

Multi-function computing devices—Multi-function computing devices 90include, for exemplary purposes only and without limitation, smartphones, tablets, cellular phones, laptops, desktops, webcams, smart TVcamera devices (and other appliance camera devices), and/or similardevices. Such devices may passively contribute (e.g., periodicallygather informatics and communicate it to management module 105 withoutuser action) and/or actively contribute (e.g., the user shouldproactively gather data and/or proactively send the data after it hasbeen gathered, the gathering being proactive and/or passive).

With exemplary sensors 90 and cameras 92 identified and brieflydescribed above, and as will be further discussed below, it is to begenerally understood an insurance customer's agreement to install and/orallow sensors 90 usage, and/or sharing of informatic data relating to adwelling, may be related to an insurance company's decision to change asetting of the insurance policy in such a way as to benefit thecustomer. In another embodiment, sensors 90 and cameras 92 preferablyrecord certain data parameters relating to products and servicesprovided by an insurance carrier to determine and/or utilize discoveredinformation, such as by amending or proposing to amend the terms of aninsurance policy alterations and other value added services such asthose described below. It is to be understood and appreciated theaforementioned sensors 90 and cameras 92 may be configured as wired andwireless types integrated in a networked environment (e.g., WAN, LAN,Wi-Fi, 802.11X, 3G, LTE, etc.), which may also have an associated IPaddress. It is to be further appreciated the sensors 90 may consist ofinternal sensors located within the structure of a structure; externalsensors located external of a structure; sound sensors for detectingambient noise (e.g., for detecting termite and rodent activity, glassbreakage, intruders, etc.); camera sensors (e.g., visible light,infrared light and/or any wavelength) such as those consisting of camerastandalone devices, or by integrating into existing camera devices in astructure. It is to be further appreciated cameras 92 be placed anywherein and around an insured property, including without limitation, on astructure, within the structure, on the ground, in the ground, on or inan artificial stand, and/or on or in a tree or other naturally createdstructures.

It is additionally to be understood and appreciated that sensors 90 andcameras 92 can be networked into a central computer hub (e.g., device300) in a dwelling to aggregate collected sensor data packets or sensors90 and cameras 92 may be communicatively connected to other sensors 90and cameras 92 and/or dwelling computing device 300 (e.g., hard wired toeither). Aggregated data packets can be analyzed in either a dwellingcomputer system (e.g., dwelling computing device 300) or via an externalcomputer environment (e.g., management module 105). Additionally, it isto be understood data packets collected from sensors 90 and cameras 92can be aggregated in dwelling computing device 300 and sent as anaggregated packet to management module 105 for subsequent analysiswhereby data packets may be transmitted at prescribed time intervals(e.g., a benefit is to reduce cellular charges in that some dwellingsmay not have Internet access or to send during low internet usagehours).

In accordance with an illustrated embodiment, in addition to thedwelling computing device 300 may additionally be coupled to a clockwhich may keep track of time for sensors 90 and cameras 92, therebyallowing a given item of data to be associated with the time at whichthe data was captured. For example, sensors 90 and cameras 92 mayrecurrently capture readings of temperature, wind speed, humidity,appliance operating times, etc., and may timestamp each reading. Thetime at which the readings are taken may be used to reconstruct eventsor for other analytic purposes, such as those described herein. Forexample, the timestamps on wind speed readings taken during a hurricanemay allow it to be determined, after the hurricane has occurred, howquickly the wind speed rose in the vicinity of the structure.

A storage component may further be provided and utilized to store datareadings and/or timestamps in sensors 90 and cameras 92. For example, astorage component may include, or may otherwise make use of, magnetic oroptical disks, volatile random-access memory, non-volatile random-accessmemory, or any other type of storage device. There may be sufficientdata storage capacity to store several hours or several weeks of datareadings. For example, the severe part of a hurricane might last forhalf a day, a full day, or several days. A storage component might havesufficient storage capacity to allow twelve or more hours of readings tobe stored, thereby allowing forensic reconstruction of how the hurricaneaffected the structure during the full time that the structure wasexperiencing the hurricane's impact.

A communication component may further be provided and utilized tocommunicate recorded information from dwelling computing device 300 toan external location, such as management module 105, which may beassociated with an insurance carrier. The communication component maybe, or may comprise, a network communication card such as an Ethernetcard, a Wi-Fi card, or any other communication mechanism. However, thecommunication component could take any form and is not limited to theseexamples. The communication component might encrypt data that itcommunicates, in order to protect the security and/or privacy of thedata. Additionally, data from sensors 90 and cameras 92, a computerizedclock and/or a storage component may be communicated directly tomanagement module 105, via network 50, thus obviating or mitigating theneed for dwelling computing device 300.

Management module 105 may include, or otherwise may cooperate with,retrieval engine 110. Retrieval engine 110 receives information fromsensors 90, cameras 92, and/or dwelling computing device 300. In oneembodiment, retrieval engine 110 sends a query to dwelling computingdevice 300 to respond with data generated by sensors 90 and cameras 92.In another embodiment, retrieval engine 110 sends a query to sensors 90to retrieve data they generated. In yet another embodiment, sensors 90and cameras 92 send data to retrieval engine 110 as the data isgenerated. In still another embodiment, sensors 90 and cameras 92 storedata and periodically (e.g., every night at 3:00 A.M.) send to retrievalengine 110. However, such is not an exhaustive list of methods ofcommunicating data from sensors 90 to retrieval engine 110, and it iscontemplated herein that data may be sent in any way as known in theart, including permutations of methods described herein. In yet anotherembodiment, retrieval engine 110 monitors which sensors 90 are activelysending data to management module 105, including which sensors 90, ifany, have been installed.

In one embodiment a single instance of management module 105 receivescommunications from sensors 90 and cameras 92 at a plurality ofstructures/locations (e.g., thousands of sensor locations communicatingto a single management module 105, thousands of camera locations eitherfrom aerial photography or from the ground communicating to a singlemanagement module 105), however it is contemplated herein that anypermutation of sensor(s) 90, camera(s) 92, and management module(s) 105may be utilized as would be readily understood by those skilled in theart.

In still another embodiment, data received from sensors 90 is utilizedto change, or consider changing the policy's settings and/or sending anotification.

Management module 105 may further include data engine 120 that analyzesdata that has been generated by sensors 90 and cameras 92. Data analysisengine 120 may apply business rules to determine if conditions have beenmet to alter terms an insurance policy, such as lowering the deductiblepayments for an insurance policy. In one embodiment, policy settings maybe changed based on the fact that sensors 90 have been installed, andthe amount/type of the change may be based on how many sensors 90 wereinstalled and/or what type of sensors 90 were installed. In anotherembodiment, policy settings may be changed based on the type and contentof data received from sensors 90.

Informatics-Based Adjustments

For exemplary purposes only, if humidity sensors 90 in the structure'sbasement detect consistently low levels of humidity, such may indicate awater-tight seal in the basement, and such may be sufficient to lowerthe deductible (e.g., lowering the deductible for all claims, orlowering the deductible for all water damage claims, or lowering thedeductible for water damage claims in the basement alone). In anotherexample, if temperature sensors 90, possibly in combination with(infrared) cameras detect that point sources of heat/fire (e.g.,candles, hot plates, toaster ovens, oven, stove, grill, space heater)are never and/or rarely operated outside the presence of an attendantperson, then such may be sufficient to lower the deductible (e.g., forall claims, for only fire damage claims, for only fire damage claimscaused by point sources of heat/fire).

In yet another example, if gas detection sensor 90 detects low and/ornon-existent levels of certain types of gasses (e.g., propane, naturalgas), such may indicate that the gas fixtures have been weldedcorrectly, and such may be sufficient to lower the deductible (e.g., allclaims, just fire-related damage claims, just fire-related damage claimscaused by the gas being tested). In still another example, if gasdetection sensor 90 detects low and/or non-existent levels of certaintypes of gasses (e.g., gasses that may leak into the basement throughthe wall such as radon) in the basement and/or the structure, such mayindicate good waterproofing of the basement and/or a lack of cracks inthe structure's support walls and foundation, and thus that may besufficient to lower deductibles (e.g., for all claims, for only gasrelated claims, for only water damage claims, for all stability typeclaims such as those related to damages caused by earthquakes).

In another example, electrical sensor 90 or plumbing sensor 90 mayindicate that the electrical system or the plumbing system,respectively, are operating (well) within normal parameters, and thussuch data may be interpreted, by data analysis engine 120, as worthy oflowering the deductible (e.g., for all claims, just claims caused by theelectrical system, just claims caused by the plumbing system).

In even another example, air pressure sensor 90, air speed sensor 90,and camera 92 may, working independently or in concert, indicate thatthe chance of a weather-related damage is low, and thus lower thedeductible. One such situation may be if air speed sensor 90 indicateshigh speed winds occur infrequently. Another such situation may be ifcamera 92 indicates that no/few trees and/or other things are withinrange of falling on the structure in the event of (severely) adverseweather. Another such situation may be if air pressure sensor 90indicates that rapid changes in air pressure are rare/infrequent, or theair pressure never/infrequently falls below a certain threshold (e.g.,980 millibars (mb), 985 mb, 990 mb, 1,000 mb).

Management module 105 may further include command generation engine 130.Command generation engine 130 may send commands to sensors 90. Suchcommands may be sent through intermediary dwelling computing device 300,or such commands may be sent directly to sensors 90. Such commands mayinclude, for exemplary purposes only and without limitation, aninstruction to take an immediate reading, an instruction to take aseries of readings (e.g., every five minutes for one hour, every minutefor one week), an instruction to take more frequent readings (e.g.,every hour rather than every six hours), an instruction to take lessfrequent readings (e.g., every day rather than every hour), and/or anypermutations or derivations thereof as will be known by those skilled inthe art.

Data engine 120 may also apply business rules to identify manualsrelated to an appliance that informatics has been communicated about,scheduling a repair for an appliance that informatics has beencommunicated about, sending a message to change a setting of anappliance that informatics has been communicated about, and/or sending amessage about a repair and/or alteration including instructions onattending to such repair and/or alteration.

In one embodiment, informatics is gathered about one or more items in ahouse, such as an appliance. The type of the appliance may be identifiedby data engine 120, and manuals relating to the appliance may beidentified and electronically sent, such as to the owner of theappliance. Particular reference to a portion of the manual may bespecifically identified and/or provided regarding an action to be taken.

In another embodiment, informatics is gathered about an appliance andthat informatics is analyzed to determine a working condition of theappliance. For exemplary purposes only, the informatics may relate to asound that the appliance is making (e.g., a clicking sound may indicatethat the appliance is broken), the informatics may relate to a length oftime that certain actions require as compared to a previous length oftime that the same or a similar action required (e.g., previously it wasfive minutes for the temperature of ambient air in a freezer tostabilize after it was opened to remove an object, but now it is sixminutes), infrared readings of the object (e.g., detecting a greaterheat leakage in the seals of a refrigerator, detecting an increased hightemperature for a dryer, detecting an increased amount of time for anobject, such as a washing machine, to cool down). Based on the gatheredand analyzed informatics, a repair service appointment maybe scheduled.It is also contemplated that once repair service is necessary aninsurance company such as USAA can assist the owner of the appliance inscheduling the appointment using a contractor network or other networkknown to by the insurance company.

In another embodiment, based on the gathered and analyzed informatics, amessage may be sent that recommends and identifies a setting change foran appliance (e.g., reduce HVAC burden, increase operating temperatureof refrigerator because of sub-optimally performing cooling mechanism).It is also contemplated that advice and guidance can be provided to theinsured by the insurance company based upon the gathered analyzedinformatics about the appliance. This advice and guidance can be used tohelp extend the life of the appliance or help with scheduledmaintenance.

In another embodiment, the informatics gathered using data engine 120and this data can be compared to how the appliance is intended toperform as prescribed by the manufacturer. This information can begathered from the manufacturer, from the manuals about the appliance, orother sources. When the appliance does not perform as intended by themanufacturer the insurance company or the appliance owner can bealerted. For example, the washing machine is intended to use X amount ofwater per minute. But the sensor in the appliance determines that ahigher than acceptable amount of water is being consumed this couldindicate that the appliance is in need of repair and is in danger ofbreaking and causing water damage to the surrounding area.

In still another embodiment, a work project is identified based ongathered informatics. For exemplary purposes only, the work project maybe painting a wall, creating an addition, replacing an appliance,finishing drywall, waterproofing a basement, and replacing and/orupgrading a roof. Subsequent to data engine 120 determining andidentifying the work project, that determination may be utilized toinform and/or cause future decisions/recommendations.

In yet another embodiment, sensors can determine if recoverabledepreciation in a claim for a covered loss can be provided to theinsured. An example of how this could occur is a sensor 90 can sendnotification to the data engine 120 that the insured has replaced,repaired or maintained an item in question with like kind and quality oritem(s) of similar quality and usefulness. When this happens, theinsurance company is notified and can provide the insured recoverabledepreciation.

Camera-Based Adjustments

In some embodiments, the data analysis engine 120 may also analyze datathat has been generated by cameras 90. As such, the data analysis engine120 may utilize received imagery to determine conditions that exist atthe insured property, changes to conditions, hazards to the dwelling,material recognition, object recognition, and/or, possibly with thecooperation of policy analysis engine 140, compare the determinedconditions to an insurance policy.

In one embodiment, imagery is gathered by cameras 90. Such cameras maydetect visible and/or infrared light, may record 2D or 3D imagery, andmay record thermal imagery. Further, it is contemplated herein that analready installed camera that has been redesigned and/or reconfigured tofunction with the embodiments described herein.

In another embodiment, the imagery is analyzed to determine if vandalismhas occurred. This analysis may include identifying a change of colorbetween a recent image and an image previously taken. Or the analysismay include identifying a change in the moisture level using thermalimagery. This analysis may also include identifying a change to thestructure (e.g., a hole in a wall), which may include merely analysis of2D imagery, may include analysis of 3D imagery, and/or it may includeanalysis of thermal imagery.

In yet another embodiment, the imagery is analyzed to determine if analteration has been made to the property. The alteration detected mayinclude replacing/adding/removing an appliance, adding/renovating aroom, and/or enlarging a room. The alteration may also include damage,such as damage caused by a weather event. The damage caused by a weatherinvent may include damage to a structure (e.g. window knocked out orcracked, roof torn apart, a wall with a hole, a wall that has beenknocked over, and damage to a wall). The analysis may be conducted byviewing a single image, thermal image, by viewing several images takenapproximately contemporaneously, comparing image(s) to previous imagesto detect changes, comparing image(s) to the terms of an existinginsurance policy, and comparing image(s) to the terms of an applicationfor an insurance policy.

In one or more embodiment, multiple pictures may be taken and stored forany period of time, up to and including permanent storage.

In another embodiment, imagery is analyzed through object recognition todetermine a value for an object in the imagery (e.g., the value of apiece of jewelry, the value of an appliance, such as a TV). The visuallyappraised value may be compared to previous imagery of that object, suchas to detect a change in “current” value. The visually appraised valuemay be compared to the terms of an insurance policy, and/or the visuallyappraised value may be compared to an application for an insurancepolicy. For exemplary purposes only, imagery may have utilized to detectand calculate the visually appraised value for one or more objects in astructure (up to and including all objects in the structure), comparethe visually appraised value(s) to the terms of an insurance policy, andpotentially send a notification if the visually appraised values exceedthe terms of the insurance policy. Similarly, a notification may be sentif the visually appraised value exceeds the terms in an application foran insurance policy.

In another example, the camera images of the dwelling, gathered eitheron the ground by the insured, the insurance company, or a 3rd party ortaken through aerial imagery can use object recognition to categorizethe dwelling characteristics to visually appraise the replacementrebuild cost value or market value of the dwelling. The visuallyappraise the replacement rebuild cost value or market value of thedwelling can be without objects/items within the property or withobjects/items within the property. The corresponding analysis andcomparison to insurance may indicate whether to send a notification tothe insured so that the insurance amount can be adjusted. The insurancecompany can also use this information captured to automatically adjustthe insurance amount either at the policy issue, when the image isgathered, when the image is provided to the insurance company, or at thenext policy renewal. In still another embodiment, the imagery may beanalyzed to determine a number of occupants of the residence and/or thehabits and trends of occupants in a dwelling. For example, the imagerymay be focused on identifying when certain individuals leave a dwelling,and these times could be correlated with the time of the day (e.g., if aperson arrives before midnight and leaves after 5 A.M., they may bepresumed to have slept there). Continuing this example, the system maycount how often certain individuals sleep at the dwelling, and comparethat to a threshold (e.g., 10 times in a month, 30 times in a 3-monthperiod, 100 times in a year). Still continuing this example, rather thanidentify specific individuals, the system may merely track the number ofpeople that sleep in the dwelling, and based on that informationdetermine how many occupants reside in the dwelling.

In another example, the imagery may be focused on determining the numberof hours individuals are in the dwelling (whether it be daytime ornighttime), and based on that information determine how many occupantsreside there. Similar to the other example, the analysis may be focusedon distinguishing between people to identify who is within the dwelling,or the analysis may be focused on merely counting how many people arewithin the dwelling.

Continuing with this embodiment, the occupant count may be comparedagainst an insurance policy and/or an application for the same. Based onthe comparison, a notification may be sent (e.g., if the policydescribes three occupants, but there appear to be nine occupants, then anotification may be sent to the insurer). Further, it is contemplatedherein that “occupants” may include people and/or pets.

In even another embodiment, the location of a heat source (e.g., candle,toaster oven, oven, stove, hot plate, electric kettle, space heater,water heater, appliance, electric charger) may be determined, such as byanalyzing a 3D infrared image and/or by analyzing one or more infraredimages. In one example, the temperature of a nearby item (e.g., woodenshelf) is measured when the heat source is not activated (e.g., unlitcandle, room temperature oven, stove, hot plate, kettle, heater,appliance, electric charger). Subsequently, when the heat source isactivated, the temperature of the nearby item is again measured. Basedon a comparison between the two temperature measurements, a notificationmay be sent. Alternatively, a notification may be sent based on solelythe temperature of the item when the heat source is activated. In yetanother alternative, a notification may be sent based on a combinationof the comparison and the second temperature.

In another embodiment, a distance between a heat source and an object isdetermined, and based on a comparison of the distance and apredetermined threshold (e.g., two feet) a notification may be sent.Alternatively, the predetermined threshold distance may be associatedwith the temperature of the heat source (e.g., 200 degrees means thethreshold is one foot, 250 degrees means the threshold is two feet).Continuing with this alternative, the threshold distance may be based on(1) the temperature of the heat source, and (2) the flammability of thenearby object (e.g., the threshold distance is three feet for 200degrees and if the nearby object is paper, and the threshold distance isone foot for 200 degrees and if the nearby object is metal).

It is contemplated that the location of any object, heat source orotherwise, may be calculated based on imagery such as, for exemplarypurposes only and without limitation, a 3D image, one or more images(visible light, infrared, or otherwise). Thus, for example, the distancebetween a heat source and an object may be calculated based on firstidentifying/calculating the location of both the heat source and theobject.

It another embodiment, a heat source is identified. For example, if anobject is a higher temperature than surrounding objects, and ameaningful temperature differential is maintained, data analysis engine120 may identify the object as a heat source. Further, if the heatsource is moved, data analysis engine 120 may identify a new locationfor the heat source. Along those lines, and continuing the example, ifthe heat source is moved closer to an object, or if an object is movedcloser to a heat source, system 100 may compare a predeterminedthreshold to the new distance between the heat source and the object,and, based on the comparison, send a notification. The notification mayinclude, for exemplary purposes only and without limitation, an alert toa person associated with the structure (e.g., owner and/or resident), analert to the insurance company that unsafe conditions may exist, and/ora combination thereof.

Another embodiment could include using an analysis engine 120 associateto the camera images of the inside or outside the dwelling that canrecognize risks in the exterior or interior of the home. When these areidentified the insurance company can provide advice and mitigationopportunities to the insured so that the chance of damage is reduced.For example, the camera image can identify that the insured has a treebranch touching the roof which can cause the roof to wear quickly whenthe branch moves and rubs against the roof. The analysis engine 120could identify this and the insured would be notified that there is arisk and how to correct the risk. The camera images collected in theanalysis engine 120 could also be used for acceptability, underwriting,and pricing.

In another embodiment, the camera could be fixed to an airplane, UAV,satellite or another device that will allow images from the sky abovethe home. These images can capture roof geometry, roof material,exterior siding material and other features about the home. These imagescan be used to establish how much to insure the home, risks associatedand more. The camera images from above the home can identify riskhazards like hail damage to the roof and allow the transmission of thisinformation to the insurance company. The insurance company can use thisinformation, like whether the home has previous hail damage to the roof,to help with the underwriting and acceptability guidelines.

Another embodiment could include the insured, insurance company, or a3rd party company taking pictures of the dwelling using a Smartphone ofother camera that can capture metadata like the GPS coordinate,direction, etc. The insurance company can use the camera images capturedto create a digital blueprint of the home. This digital blueprint can beused to create a graphical representation of the home for use by theinsurance company. It can be used to display the digital blueprint tothe insured on the company's website or other portals to the insured.The digital blueprint can also be saved to help with claims handling ifthere is a claim on the home. The insurance company can look at thepictures and location of objects in the home and know what the pre-lossstatus of the home was so that the insurance company can help theinsured restore the home to pre-loss status. Another use of the cameraimages for the digital blueprint can be to develop an insurance amounton the home. The camera images can have object recognition capabilitiesand know whether the countertop is, for example, granite or concrete anduse this information to establish an insurance amount.

Management module 105 may further include command generation engine 130.Command generation engine 130 may send commands to sensors 90 andcameras 92. Such commands may be sent through intermediary dwellingcomputing device 300, or such commands may be sent directly to sensors90 and cameras 92. Such commands may include, for exemplary purposesonly and without limitation, an instruction to take an immediatereading, an instruction to take a series of readings (e.g., every fiveminutes for one hour, every minute for one week), an instruction to takemore frequent readings (e.g., every hour rather than every six hours),an instruction to take less frequent readings (e.g., every day ratherthan every hour), an instruction to change the location and/or shootingangle of camera 90, and/or any permutations or derivations thereof aswill be known by those skilled in the art.

Management module 105 may further include policy engine 140. Policyengine 140 may analyze the data such as described above with respect todata engine 120. It is contemplated herein that data engine 120 andpolicy engine 140 may work in cooperation/tandem, independently of eachother, without interaction with the other, or any other permutations orderivations thereof as will be known by those skilled in the art.

In one embodiment, policy engine 140 accesses a database that containsinformation about insurance policies and/or applications for insurancepolicies. However, it is contemplated herein that policy engine 140 mayaccess/retrieve/receive said information by any means as known by thoseskilled in the art.

In another embodiment, policy engine 140 is responsible for some(including, in some embodiments, all) of the comparison betweeninsurance information and information gleaned from imagery.

Upgrade Sensors

For exemplary purposes only, in one embodiment, if an insurance customeragrees to install and/or upgrade a sensor 90 at an insured property,then the policy may be eligible for a policy setting change.

In one or more embodiments, the policy setting change may include, forexemplary purposes only and without limitation, lowering a deductiblepayment for an entire insurance policy, lowering a deductible paymentfor one or more aspects of an insurance policy, lowering a premium foran insurance policy, increasing a coverage amount for an insurancepolicy (e.g., for the entire policy, for just one or more aspects of thepolicy), adding a coverage area (e.g., adding water damage), andadjusting a coverage type (e.g., adjusting a policy that just coverswater damage from leaky pipes and adjusting it to also cover flooddamage, such as from weather events).

In another embodiment, a customer enrolls in a policy and/or policychange whereby if/when they agree to install a sensor 90 at an insuredproperty, the customer's insurance policy may be affected by aninsurance policy setting change. The customer may enroll in the policy(change) via receiving an invitation to enroll, and accepting thatinvitation.

In yet another embodiment, if/when the customer agrees to a change tothe sensor(s) 90, a second policy setting change is implemented. Forexemplary purposes only, the customer may agree to upgrade a sensor 90already onsite (e.g., upgrading a camera 92 to measure both infrared andvisible light), the customer may agree to add an additional sensor 90(e.g., adding a second camera 92).

In still another embodiment, the type and/or amount of the change to theinsurance policy is, at least in part, based on the sensor 90 that wasinstalled and/or upgraded. For exemplary purposes only and withoutlimitation, if the sensor 90 is an infrared camera 92 the policy changemay be more beneficial for the customer than if the sensor 90 is avisible light camera, or if the camera 92 is 3D the policy change may bemore beneficial than if the camera 90 is 2D, or a combination of sensors90 (e.g., motion, visible light and infrared) at certain locations(e.g., at every opening such as a door or window) may cause a policysetting change that is more beneficial to the customer than if thecoverage is less thorough.

In yet another embodiment, the type and/or amount of the change to theinsurance policy may be, at least in part, based on a certain percentageof the insured structure and/or the surrounding area that the sensorscan detect (e.g., 20%). In this embodiment, there may be thresholds ofcoverage that cause certain policy setting changes.

Further continuing with this embodiment, different sensors may beweighted different amounts. For exemplary purposes only, a 2D visiblelight camera may be weighted to count as 20%, a 3D visible light cameramay be weighted to count as 30%, an infrared camera may be weighted tocount as 15%, a 3D infrared camera may be weighted to count as 25%, anda motion sensor may be weighted to count as 10%. Continuing with theseexamples, if a 2D visible light camera detects 50% of the insuredproperty, given that, in this example, 2D visible light cameras areweighted at 20%, the weighted coverage amount of coverage is 10% (i.e.,50% times 20%). Still continuing with this example, if a 3D visiblelight camera and a 3D infrared camera each detect 50% of the insuredproperty, the total weighted coverage amount of coverage is 27.5% (i.e.,50%*30%+50%*25%). The (total) weighted coverage amount may be comparedto a threshold (e.g., 5%, 10%, 25%, 50%) to determine the type and/oramount of the policy's setting change.

Management module 105 may further include policy engine 140. Policyengine may implement changes to a policy's settings based on, forexemplary purposes only, if the customer agreed to sensors beinginstalled/utilizing/upgraded, how many sensors are being utilized, acoverage amount of the sensors. Policy engine 140 may also analyze thedata such as described above with respect to analysis engine 120. It iscontemplated herein that analysis engine 120 and policy engine 140 maywork in cooperation/tandem, independently of each other, withoutinteraction with the other, or any other permutations or derivationsthereof as will be known by those skilled in the art.

Warranties

Management module 105 may further include data engine 120 that analyzesdata that has been generated by sensors 90. Data engine 120 may applybusiness rules to determine if conditions have been met to generateand/or alter terms of a warranty.

It is contemplated herein that informatics may include any informationthat may be generated by sensors described herein. For exemplarypurposes only and without limitation, such informatics includes thecleanliness of the target object (i.e., the object being considered forwarranty), the cleanliness of a second object (i.e., an object otherthan the one being considered for warranty), the cleanliness of one ormore floors in the structure, the cleanliness of one or more windows inthe structure, the cleanliness of one or more surfaces in the structure(e.g., countertop), the average temperature in the structure, theaverage temperature outside the structure, the humidity in thestructure, the detection of gasses in the structure, harmful (e.g.,radon, carbon monoxide) or otherwise (carbon dioxide, nitrogen), anamount of motion in the structure, such as in the proximate vicinity ofthe target object, the conditions of the plumbing system, such ascompared against the expected and/or calculated stress tolerancethresholds for the plumbing system, wind speed inside or outside thestructure, air pressure (changes) inside or outside the structure, theconditions of the electrical system, such as compared against theexpected and/or calculated stress tolerances of the electrical system,information about the structure's stability, information related to airborn particles, such as mold, or information related to light (e.g.,visible light, infrared, radar).

In one example, informatics about an appliance is utilized to inform theterms of a warranty for the appliance. In another example, informaticsabout a structure is utilized to inform the terms of a warranty for anappliance. In still another example, informatics about a first object isutilized to inform the terms of a warranty for a second object.

In another example, an appliance type is selected (e.g., appliancesgenerally in the kitchen). For a given structure, informatics isgathered about one or more objects at the structure that are of theselected appliance type. A condition score for the appliance type atthat structure is generated, and based on the appliance-type score,warranty terms are generated.

In yet another example, informatics are gathered about the target object(for this example, a washing machine) as well as a second object (forthis example, a clothes dryer). A condition score is generated for bothobjects. A relationship score is also generated for both objects, therelationship score indicating how closely related those objects are(e.g., in terms of how common it is for conditions of one to bereflective of the other's condition). A warranty for the target objectis generated, and the terms of the warranty is based at least in part on(1) the condition score for the target object, and (2) the combinationof (2a) the condition score for the second object and (2b) therelationship score. It is contemplated herein that the terms of thewarranty may be 75% based on #1 and 25% on #2; 50% for #1, 25% for #2,and 25% for other factors, or any combination as would be recognized byone skilled in the art.

In one embodiment, a warranty includes a beginning time (e.g., now, thefirst of the month, after a previous warranty expires), an ending time(e.g., indefinite, some period of time after the beginning), a premium(e.g., a monthly payment offered by the owner of the object covered bythe warranty), a coverage amount (e.g., replacement of the object forsomething of equivalent value, replacement of the object for a new(er)similar object, the value of the object at the beginning of thewarranty, the value of the object when it is damaged/totaled), andcoverage terms (e.g., only mechanical damage, any type of damage).

Detection-Based Adjustments

Management module 105 may further include data engine 120 that analyzesdata that has been generated by detection devices 90. Data engine 120may apply business rules to determine if damage has occurred, notify aninsured party of changed conditions, communicate a coverage amount tothe insured party, recommend a contractor to conduct repairs and/orupgrades, schedule a repair and/or upgrade, and/or recommend an upgrade.

For exemplary purposes only, in one embodiment, sensors 90 (e.g.,detection devices) are utilized at an insured property. Sensors 90 maybe installed at the insured property for utilization with system 100,they may be reconfigured to work in cooperation with system 100, andthey may include personal computing devices (e.g., smart phone, tablet).Informatics from sensors 90 may be analyzed by data engine 120 todetermine, for exemplary purposes only, what item was damaged (e.g., awall, a window, a roof, an appliance, furniture), what type of damageoccurred (e.g., fire damage, flood damage, rain damage, wind damage),and/or when the damage occurred (e.g., a specific time and/or a range orplurality of times).

In another embodiment, after an event is detected by sensors 90, anotification may be sent to the insured party. For exemplary purposesonly, it is contemplated herein that an event may include, damage to theproperty, a structure on the property, and/or objects in the structure,and/or detecting specified information (e.g., a water level in thebasement's sump that is above a threshold, a temperature differencebetween different portions of the structure, and a (sustained) humiditylevel in one or more parts of the structure).

In yet another embodiment, an amount of insurance coverage is determinedand that amount is optionally communicated to the insured party. Forexample, if it is detected that the basement flooded, policy engine 140may analyze and determine if coverage exists and an amount of coverage(e.g., $500,000.00) that the insured party has for water damage and/orflood damage; such information may optionally be communicated to theinsured party and/or identified recipients (e.g., otherresidents/employees at the insured property). Further, it iscontemplated herein that the notification of the event and the amount ofcoverage may be sent in the same message or successive messages.Continuing with this example, if the basement flooded, policy engine 140may identify a section of an insurance policy that relates to the waterdamage, and language from that section may be sent and/or paraphrasedand sent to the insured party. It is important to note, that when thenotification is sent, that it explains the policy and if it would orwould not be a covered loss based on the cause of loss.

In even another embodiment, after damage is detected via informatics, arecommendation for a contractor repair party may be generated and sentto the insured party. The recommendation may be at least partly based onthe damage amount and/or type. For example, if the damage was a leakypipe that flooded a bathroom and leaked into the floor below, onerecommendation may be for a plumber to fix the pipe (however explainingthat based on the cause of loss, the pipe repair itself may not becovered by insurance), and another may be for a general contractor tofix any damage resulting from the water (in this example tworecommendations are generated and sent to the insured party, but it iscontemplated herein that a single event may lead to any number ofrecommendations, including one or more). Further, the recommendation maybe at least partly based on the coverage amount for the detected damage.For example, if the coverage amount is relatively high, then both aplumber and general contractor would be called. However, if the coverageamount is lower, then perhaps only the plumber would be called, orperhaps a less-expensive plumber would be called.

In another embodiment, and continuing with the water damage examplesolely for simplicity and continuity, the repairing party (e.g.,plumber, general contractor) may be contacted at contractor computingdevice 300 with a message. The message may include, for exemplarypurposes only, the location of the insured property (e.g., streetaddress), the location of the damage in the house (e.g., the first floorbathroom), the type of damage, the items damaged (e.g., floor, walls),an estimated amount for the cost to repair, a pre-authorized amount ofwork that the contractor is authorized to perform (e.g., up to $750 inlabor and $175 in parts, explaining what is covered and what isexcluded), and a request for available times. Continuing with thisembodiment and example, one or more available time periods for thecontractor may be forwarded to the insured party, and the insured partymay confirm and/or select one of the time periods to schedule repairs.Thus, the insured party's response is received by system 105 (e.g., atext, an email, a phone call to a representative at an insurancecompany), and subsequently, the contractor is confirmed to conductrepairs at the selected/confirmed time period. Such confirmation mayinclude a legally binding obligation, by the insurance company to thecontractor, to pay the contractor for the relevant work and parts forwhat is covered under the policy.

Alternatively, it is contemplated herein that the customer may propose atime or a time period that is communicated to one or more contractors,and subsequently one of the contractors agrees to the time or timeperiod for repairs.

In another embodiment, detection devices 90 may detect a condition thatwarrants proactive adjustments by the insured party. In one example,sensors may detect that the water level in and around a basement (e.g.,a basement's sump) is rising above a threshold, and that the insuredparty should improve their sump pump (e.g., increase its bandwidth,lower the level it draws water from). In another example, the sensorsmay detect the capacity of a hot water heater (e.g., 50 gallons), andthey may further detect that a small amount of that water is utilized(e.g., over a three month period there is never less than 25 gallons ofhot water remaining), and based on that information, a notification maybe sent to the insurance company and/or the insured party that theworking capacity of the hot water heater may be reduced.

In still another embodiment, an electronic interface is provided bymanagement module 105. The interface may provide historical, real-time,and/or near real-time display of data readings by detections devices(e.g., which lights are on, which motion detectors have detectedmovement how recently, which cameras have detected movement howrecently, which cameras have detected which people how recently, a chartof humidity levels, a chart of temperature readings, a chart ofavailable hot water, an identification of when and how often whichelectrical circuits are utilized at or near capacity, and/or a(persistently) increasing amount of harmful gasses detected even if theamount detected is currently below a predetermined dangerous threshold).

In even another embodiment, upon informatics being sensed by detectiondevices 90 and communicated to management module 105, policy engine 140may immediately start generating an insurance claim. Subsequently, theinsured party may be notified that an insurance claim is processed, andthe notification may include, for exemplary purposes only and withoutlimitation, a description of the damage, images of the damage, therelevant portion of an insurance contract/provision, the amount ofcoverage (to include any explanation of recoverable depreciation), anycoverage exclusions, and a financial instrument that covers the insureddamages (it is contemplated herein that the check may include cash, acheck, a direct deposit, or any other means of transferring money asknown by those skilled in the art).

Policy Term Adjustments

Data engine 120 may also apply business rules to determine terms of apolicy, the terms including, for exemplary purposes only and withoutlimitation, a coverage amount of the policy, a time period for thepolicy, and an identification of items and/or structures covered by thepolicy.

For exemplary purposes only, in one embodiment, detection sensors maydetect a sticker and/or label on an item, such as an appliance, that isconsistent with warranty coverage for the item. The label may identify acoverage for the item (e.g., language such as “three-year warranty”)and/or the label may identify a repairing party and when the repairswere performed (in which case, the parts that were worked on may becovered by a warranty provided by the repairing party).

In another embodiment, informatics gathered by detection devices 90 mayindicate and/or identify a repairing party, and such informatics mayfurther indicate and/or identify an item that the repairing party workedon.

In still another embodiment, the value of one or more items iscalculated based on the informatics. For exemplary purposes only, thevalue of the item may be calculated based on the visual appearance ofthe item, the ability of the item to manage and dispense heat (e.g.,what temperature a washing machine gets to, which parts of the washingmachine get to what temperature, how quickly it cools down, which nearbyparts have their temperature affected by it). Continuing with thisexample, if any of the measurements, such as temperature measurements,are outside of a predetermined threshold, then the estimated value ofthe item is thus reduced.

In even another embodiment, the value of one or more structures isestimated, the structure(s) being covered by an insurance policy. Thevalue of the structure(s) may be estimated based on visual appearance ofthe structure, data gathered by one or more air sensors (e.g., whetherspores and/or contaminating elements are detected), the value of one ormore appliances in the structure(s), and/or the performance of one ormore items/appliances in the structure. The informatics may be analyzedto determine a potential liability for the structure(s) and/oritems/appliances, and that potential liability may be utilized toidentify a term, such as a coverage amount, of a warranty and/orinsurance policy relating to the structure(s) and/or items/appliances inand around the structure(s).

In another example, electrical sensor 90 or plumbing sensor 90 mayindicate that the electrical system or the plumbing system,respectively, are operating (well) within normal parameters, and thussuch data may be interpreted, by data engine 120, as indicative ofinsurance coverage for water damage and/or fire/electrical damage.

Score-Based Adjustments

Management module 105 may further include data engine 120 that analyzesdata that has been generated by sensors 90. Data engine 120 may applybusiness rules to determine if conditions have been met to configureand/or re-configure terms to an insurance policy (e.g., such as a policyfor a structure wherein the informatics are related to another structureand/or a vehicle).

For exemplary purposes only, informatics that relates to a firstproperty may be utilized to determine a score, which is utilized togenerate one or more terms of an insurance policy for a target property.It is contemplated herein that both first and target property may eachbe residential properties, commercial property, industrial properties,vacant lots, and/or any manifestation of real property as would berecognized by those skilled in the art. It is further recognized that afirst property may be something other than real property, such as, forexemplary purposes only and without limitation, an appliance and avehicle (e.g., car, truck, motorcycle, air vehicle, water vehicle).

In one embodiment, the informatics relates to a cleanliness of the firstproperty, a structural element at the first property (e.g., basement,roof, wall) and/or an item at the first property. Alternatively, theinformatics may relate to the structural integrity of dwelling or itemand the maintenance performed regarding the upkeep of a dwelling,portion thereof or item located therewithin. Pursuant to the cleanlinessscenario, it is contemplated herein that cleanliness may relate to howoften at least part of the first property is cleaned, how generallyclean the item is, and how often and/or quickly the item gets dirty. Itis further contemplated herein that the cleanliness determination may bemade based on measurements from, such as, for exemplary purposes onlyand without limitation, sensor 90 that detects visible light, sensor 90that detects infrared light, sensor 90 that detects particles and/orgasses, and/or sensor 90 that detects wind speed. For example, if anitem is generally cleaner than a predetermined threshold, or if the itemgets dirty slower than a predetermined rate, the score upon which thepolicy terms are based may indicate that the terms will be morefavorable to the insured.

In another embodiment, the informatics relate to a working condition ofan item, such as an appliance, at the first property. For exemplarypurposes only, this may be determined by an analysis of how theappliance looks (e.g., visible light, infrared light), an analysis ofsounds that the appliance does and/or does not make, an analysis ofwater/electrical input to the appliance, an analysis of water outputfrom the appliance, an analysis of heat output from the appliance, andan analysis of air particle output, or lack thereof, from the appliance.

In another embodiment, the informatics relates to the age of anappliance at the first property. The age may be determined via any meansas described herein and as would be recognized by those skilled in theart. The score upon which policy terms are determined may be based onthe appliance's age, or the score may be determined as follows. Forexemplary purposes only, a type for the appliance may be identified(e.g., washer, dryer, laundry machine), and based on that type one ormore age ranges may be identified. For example, for a washing machinethe age ranges may be 0-3 years “New”, 3-9 years “Intermediate age”,9-15 years “Old”, and 15+ years “Ancient”. Based on which age range theappliance's age falls within, the policy's terms may be adjusted eitherfor or against the insured's benefit. As in, if the appliance's age iswithin the “New” range, the insurance policy for the target property maybe adjusted to be more beneficial for the insured (e.g., lower premiums,higher coverage amount, lower deductible, more coverage categories). Itis contemplated herein that the age ranges may be any time periods, andit is further contemplated that the number of age ranges may be fourand/or any other number of age ranges.

In another embodiment, informatics at the first property indicates thatwork is being performed at the first property (e.g., necessarystructural repair, optional structural repair, remodeling). Based onthis information, the resultant terms of the insurance policy for thetarget property may be adjusted. For exemplary purposes only, ifoptional structural repairs and/or a remodeling is performed at thefirst property, the insurance policy terms may be adjusted so as to bemore beneficial for the insured, and/or if necessary structural repairsare performed at the first property, the insurance policy terms may beadjusted so as to be less beneficial for the insured. It is contemplatedherein that an optional structural repair and/or remodeling isidentified based on the heretofore previous working condition and/orstability of the previous appliances, items, and/or structuralcomponents.

In another embodiment, informatics may relate to a vehicle. The sensorthat collects informatics from the vehicle may be placed on/in thevehicle, and/or the sensor may be placed on a structure and/or property.Independent of the sensor's placement, informatics about the vehicle maybe utilized to determine and/or adjust the resultant insurance policyterms for the target property. The informatics relating to the vehiclemay include, for exemplary purposes only, the vehicle's workingcondition, the vehicle's cleanliness, and/or the vehicle's usagecharacteristics (e.g., age of most common driver, average age ofdrivers, weighted average age of drivers per time spent with the car,weighted average age of drivers per miles driven). Informatics thatindicate generally safer and/or more “well kept” characteristics mayresult in an insurance policy with terms that are more beneficial forthe insured; and conversely, informatics that indicate generally lesssafe and/or less “well kept” characteristics may result in an insurancepolicy with terms that are less beneficial for the insured.

Informatics-Based Adjustments

Referring back to the figures, FIG. 3 shows, in the form of a flow chart(process 1000), exemplary operational steps of utilizing system 100.Before turning to descriptions of FIG. 3 , it is noted that the flowdiagram shown therein are described, by way of example, with referenceto components shown in FIGS. 1-2 , although these operational steps maybe carried out in any system and are not limited to the scenario shownin the aforementioned figures. Additionally, the flow diagrams in FIG. 3shows an example in which operational steps are carried out in aparticular order, as indicated by the lines connecting the blocks, butthe various steps shown in these diagrams can be performed in any order,or in any combination or sub-combination.

With reference to FIG. 3 , starting at step 1001, detection devices,such as sensors 90, are installed at a property, such as a structure,covered by the insurance policy. In one embodiment, sensors 90 may havebeen previously installed for other reasons (e.g., security cameras) andlater re-configured to integrate with system 100. In another embodiment,sensors 90 are installed for at least the reason of integrating with andworking with system 100. In still another embodiment, sensors 90 includea combination of pre-installed sensors 90 and newly-installed sensors90.

Subsequently, information is gathered (step 1002) and received fromsensors 90 (step 1003). As discussed above, information may be sent fromsensors 90 to dwelling computing device 300, and subsequently tomanagement module 105. In another embodiment, dwelling computing device300 is not installed onsite and sensors 90 communicate directly tomanagement module 105. In yet another embodiment, dwelling computingdevice 300 is installed onsite, and sensors 90 communicate directly tomanagement module 105, through dwelling computing device, and/or acombination thereof.

Information is analyzed by management module (step 1004), such as bydata engine 120 and/or policy engine 140. In one embodiment, data engine120 considers the data and identifies appliances and their correlateddocumentation, such as repair instructions, recommends and/or schedulesrepair services, and/or provides recommendations based on a valuation ofan appliance's working condition.

In one embodiment, command generation engine 130 may send additionalcommands to sensors 90 and/or dwelling computing device 300, such as viadwelling computing device 300 and/or directly to sensors 90. Thesecommands may alter the types of measurements being performed, thefrequency of measurements, the speed/frequency in which information iscommunicated from sensors 90, and/or any other settings. Subsequent toadditional commands being sent to sensors 90, sensors 90 and/or dwellingcomputing device 300 execute and/or perform the additional commands andsend additional information to management module 105. The additionalinformation may be analyzed independent of the previously receivedinformation, and/or it may be analyzed and/or correlated with thepreviously received information.

Related information, such as, for exemplary purposes only and withoutlimitation, maintenance advice, repair instructions, operating manuals,and/or repair services, may be sent (step 1005). Finally, a message,such as, for exemplary purposes only and without limitation, operatingadvice, may be sent to the operator of the item/appliance (step 1006).

Camera-Based Adjustments

FIG. 4 shows, in the form of a flow chart (process 1010), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 4 , it is noted that the flow diagram shown thereinare described, by way of example, with reference to components shown inFIGS. 1-2 , although these operational steps may be carried out in anysystem and are not limited to the scenario shown in the aforementionedfigures. Additionally, the flow diagrams in FIG. 4 shows an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams can be performed in any order, or in anycombination or sub-combination.

With reference to FIG. 4 , starting at step 1011, a property insurancepolicy is initiated. This policy may be stored in memory 340, such asdatabase 346. In one embodiment, policy engine 140 has access to thepolicy, such as to the terms of the policy (e.g., premium, deductible,coverage amount, coverage type).

Detection devices, such as sensors 90, are installed at a property, suchas a structure, covered by the insurance policy (step 1012). In oneembodiment, sensors 90 may have been previously installed for otherreasons (e.g., security cameras) and later re-configured to integratewith system 100. In another embodiment, sensors 90 are installed for atleast the reason of integrating with and working with system 100. Instill another embodiment, sensors 90 include a combination ofpre-installed sensors 90 and newly-installed sensors 90.

Subsequently, information is received from sensors 90 (step 1013). Asdiscussed above, information may be sent from sensors 90 to dwellingcomputing device 300, and subsequently to management module 105. Inanother embodiment, dwelling computing device 300 is not installedonsite and sensors 90 communicate directly to management module 105. Inyet another embodiment, dwelling computing device 300 is installedonsite, and sensors 90 communicate directly to management module 105,through dwelling computing device, and/or a combination thereof.

Information is analyzed by management module 105 (step 1014), such as bydata engine 120 and/or policy engine 140. In one embodiment, data engine120 considers the data and identifies prospective situations that mayjustify adjusting the terms (step 1018) of an insurance policy (e.g.,lowering deductible, increasing coverage amount, lowering premium,increasing types of situations covered, adjusting one term of a specificcoverage and/or the entire policy). In this embodiment, prospectivesituations are communicated to policy engine 140, and policy engine 140decides if an adjustment to the insurance policy is warranted. This mayinclude considering the initial policy terms and, based on the initialpolicy terms, deciding if a first adjustment is allowable. This may alsoinclude considering the initial policy terms and, based on the initialpolicy terms, deciding if an additional adjustment is allowable. Thismay further include considering the current policy terms and, based onthe current policy terms, deciding if an adjustment is allowable. Thismay also include identifying a qualification deductible for the giveninformation received from sensors 90, and, if the policy's deductibledoes not match the qualification deductible, either lowering orincreasing the policy's deductible to match the qualificationdeductible.

In one embodiment, command generation engine 130 may send additionalcommands to sensors 90 and/or dwelling computing device 300 (step 1015),such as via dwelling computing device 300 and/or directly to sensors 90.These commands may alter the types of measurements being performed, thefrequency of measurements, the speed/frequency in which information iscommunicated from sensors 90, and/or any other settings. Subsequent toadditional commands being sent to sensors 90, sensors 90 and/or dwellingcomputing device 300 execute and/or perform the additional commands andsend additional information to management module 105 (step 1016). Theadditional information may be analyzed independent of the previouslyreceived information, and/or it may be analyzed and/or correlated withthe previously received information (step 1017).

In one embodiment, information received at management module 105 isimmediately analyzed and then discarded. In another embodiment theinformation is analyzed and stored temporarily. In yet anotherembodiment, the information is stored for later analysis. And in stillanother embodiment, the information is stored via anotherdevice/module/engine.

If the customer qualifies for an adjustment to the insurance policy, inone embodiment policy engine 140 adjusts the policy's terms andoptionally subsequently notifies the customer and/or the insurer. Inanother embodiment, the policy engine 140 sends a notification that thecustomer qualifies for a policy term adjustment, the notification beingsent to the customer and/or the insurer.

FIG. 5 shows, in the form of a flow chart (process 1020), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 5 , it is noted that the flow diagram shown thereinare described, by way of example, with reference to components shown inFIGS. 1-2 , although these operational steps may be carried out in anysystem and are not limited to the scenario shown in the aforementionedfigures. Additionally, the flow diagrams in FIG. 5 shows an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams can be performed in any order, or in anycombination or sub-combination.

With reference to FIG. 5 , starting at step 1021, a property insurancepolicy is initiated. This policy may be stored in memory 340, such asdatabase 346. In one embodiment, policy engine 140 has access to thepolicy, such as to the terms of the policy (e.g., premium, deductible,coverage amount, coverage type).

Cameras 92 are installed at a property, such as a structure, covered bythe insurance policy (step 1022). In one embodiment, cameras 92 may havebeen previously installed for other reasons (e.g., security cameras) andlater re-configured to integrate with system 100. In another embodiment,cameras 92 are installed for at least the reason of integrating with andworking with system 100. In still another embodiment, cameras 92 includea combination of pre-installed cameras 92 and newly-installed cameras92.

Subsequently, information, such as imagery, is received from cameras 92(step 1023). As discussed above, information may be sent from cameras 92to dwelling computing device 300, and subsequently to management module105 (step 1024). In another embodiment, dwelling computing device 300 isnot installed onsite and cameras 92 communicate directly to managementmodule 105. In yet another embodiment, dwelling computing device 300 isinstalled onsite, and cameras 92 communicate directly to managementmodule 105, cameras 92 communicate to management module 105 throughdwelling computing device 300, and/or a combination thereof.

Information is analyzed by management module (step 1025), such as bydata analysis engine 120 and/or policy engine 140. The situations may becompared to insurance policy information as provided by policy analysisengine 140 (step 1026). In one embodiment, data analysis engine 120considers the images and identifies prospective situations such asdescribed herein (step 1027). Finally, based on the comparisons and/oranalysis, notifications may be sent (step 1028).

In one embodiment, command generation engine 130 may send additionalcommands to cameras 92 and/or dwelling computing device 300, such as viadwelling computing device 300 and/or directly to cameras 92. Thesecommands may alter the types of imagery being taken/recorded, thefrequency of image captures, the speed/frequency in which images arecommunicated from cameras 92, and/or any other settings. Subsequent toadditional commands being sent to cameras 92, cameras 92 and/or dwellingcomputing device 300 execute and/or perform the additional commands andsend additional information to management module 105. The additionalinformation may be analyzed independent of the previously receivedinformation, and/or it may be analyzed and/or correlated with thepreviously received information.

Upgrade Sensors

FIG. 6 shows, in the form of a flow chart (process 1030), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 6 , it is noted that the flow diagram shown thereinare described, by way of example, with reference to components shown inFIGS. 1-2 , although these operational steps may be carried out in anysystem and are not limited to the scenario shown in the aforementionedfigures. Additionally, the flow diagrams in FIG. 3 shows an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams can be performed in any order, or in anycombination or sub-combination.

With reference to FIG. 6 , starting at step 1031, a property insurancepolicy is initiated. This policy may be stored in memory 340, such asdatabase 346. In one embodiment, policy engine 140 has access to thepolicy, such as to the terms of the policy (e.g., premium, deductible,coverage amount, coverage type).

A change to the insurance policy's settings may be offered to thecustomer in exchange for installing/utilizing a sensor at an insuredproperty (step 1032). Subsequently, the customer may agree to theexchange and communicates the agreement to the insurance company (step1033).

Detection devices, such as sensors 90, are installed/upgraded at aproperty, such as a structure, covered by the insurance policy (step1034). In one embodiment, sensors 90 may have been previously installedfor other reasons (e.g., security cameras) and later re-configured tointegrate with system 100. In another embodiment, sensors 90 areinstalled for at least the reason of integrating with and working withsystem 100. In still another embodiment, sensors 90 include acombination of pre-installed sensors 90 and newly-installed sensors 90.

Subsequent to the sensors' 90 installation, the policy's settings areadjusted (step 1005), preferably, although not necessarily, to thecustomer's benefit. It is contemplated herein that the settingsadjustment may be performed subsequent to the agreement and before thesensors' 90 installation, although it is recognized herein that thetiming of (1) the settings change, (2) the agreement, and (3) sensorinstallation, may be any combination as would be recognized by thoseskilled in the art. Based upon business rules by the insurance companythe change to the insured policy could occur backdated to the start ofthe current policy effective date, the day the sensors were installed orat the next renewal.

Subsequently, information is received from sensors 90 (step 1036). Asdiscussed above, information may be sent from sensors 90 to dwellingcomputing device 300, and subsequently to management module 105. Inanother embodiment, dwelling computing device 300 is not installedonsite and sensors 90 communicate directly to management module 105. Inyet another embodiment, dwelling computing device 300 is installedonsite, and sensors 90 communicate directly to management module 105,through dwelling computing device, and/or a combination thereof.

In one embodiment, command generation engine 130 may send additionalcommands to sensors 90 and/or dwelling computing device 300 (step 1037),such as via dwelling computing device 300 and/or directly to sensors 90.These commands may alter the types of measurements being performed, thefrequency of measurements, the speed/frequency in which information iscommunicated from sensors 90, and/or any other sensor 90 settings.

Finally, additional sensor(s) 90 may be installed and/or sensor(s) maybe upgraded, thereby initiating a second change to the policy's settings(step 1038). It is recognized herein that any number ofagreements/installations may be combined with a similar number ofsettings changes.

Warranties

Management module 105 may further include the warranty engine 142, asmentioned above. Warranty engine 142 may analyze the data such asdescribed above with respect to data engine 120. It is contemplatedherein that data engine 120 and warranty engine 142 may work incooperation/tandem, independently of each other, without interactionwith the other, or any other permutations or derivations thereof as willbe known by those skilled in the art.

FIG. 7 shows, in the form of a flow chart (process 1040), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 7 , it is noted that the flow diagram shown thereinare described, by way of example, with reference to components shown inFIGS. 1-2 , although these operational steps may be carried out in anysystem and are not limited to the scenario shown in the aforementionedfigures. Additionally, the flow diagrams in FIG. 7 shows an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams can be performed in any order, or in anycombination or sub-combination.

With reference to FIG. 7 , starting at step 1041, sensors 90, such asdetection devices, are installed at a location. In one embodiment,sensors 90 may have been previously installed for other reasons (e.g.,security cameras) and later re-configured to integrate with system 100.In another embodiment, sensors 90 are installed for at least the reasonof integrating with and working with system 100. In still anotherembodiment, sensors 90 include a combination of pre-installed sensors 90and newly-installed sensors 90.

Subsequently, an object is identified for which a warranty may begenerated and/or reconfigured (step 1042). Informatics, such asdescribed herein, is collected by sensors (step 1043), and communicatedto management module (step 1044). As discussed herein, information maybe sent from sensors 90 to dwelling computing device 300, andsubsequently to management module 105. In another embodiment, dwellingcomputing device 300 is not installed onsite and sensors 90 communicatedirectly to management module 105. In yet another embodiment, dwellingcomputing device 300 is installed onsite, and sensors 90 communicatedirectly to management module 105, through dwelling computing device,and/or a combination thereof.

The informatics is analyzed (step 1045), such as according to businessrules and/or considerations described herein. A warranty proposal isgenerated (step 1046) and communicated to the (potential) customer, andthe warranty proposal may be a new warranty for an object, extending awarranty for an object, or changing the terms of the warranty for anobject. It is contemplated herein that a warranty may have dynamic terms(e.g., if one or more condition scores are above/below a predeterminedthreshold, the terms of the warranty improve/get worse from thecustomer's perspective). Finally, the warranty (modification) isexecuted via step 1047.

In one embodiment, command generation engine 130 may send additionalcommands to sensors 90 and/or dwelling computing device 300, such as viadwelling computing device 300 and/or directly to sensors 90. Thesecommands may alter the types of measurements being performed, thefrequency of measurements, the speed/frequency in which information iscommunicated from sensors 90, and/or any other settings. Subsequent toadditional commands being sent to sensors 90, sensors 90 and/or dwellingcomputing device 300 execute and/or perform the additional commands andsend additional information to management module 105.

Detection-Based Adjustments

FIG. 8 shows, in the form of a flow chart (process 1050), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 8 , it is noted that the flow diagram shown thereinare described, by way of example, with reference to components shown inFIGS. 1-2 , although these operational steps may be carried out in anysystem and are not limited to the scenario shown in the aforementionedfigures. Additionally, the flow diagrams in FIG. 8 shows an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams, and the various embodiments described herein,can be performed in any order, combination and/or sub-combination.

With reference to FIG. 8 , starting at step 1051, sensors 90, such asthose described and referenced herein, are installed at property. In oneembodiment, sensors 90 may have been previously installed for otherreasons (e.g., security cameras) and later re-configured to integratewith system 100. In another embodiment, sensors 90 are installed for atleast the reason of integrating with and working with system 100. Instill another embodiment, sensors 90 include a combination ofpre-installed sensors 90 and newly-installed sensors 90.

Informatics is received from sensors 90, such as informatics aboutdamage that occurred and/or an event or data that has been detected(step 1052). Subsequently, data engine 120 analyzes the informatics todetermine what event transpired (step 1053). As discussed herein,information may be sent from sensors 90 to dwelling computing device300, and subsequently to management module 105. In another embodiment,dwelling computing device 300 is not installed onsite and sensors 90communicate directly to management module 105. In yet anotherembodiment, dwelling computing device 300 is installed onsite, andsensors 90 communicate directly to management module 105, throughdwelling computing device, and/or a combination thereof.

The customer and/or selected parties are optionally notified (step1054). Policy engine 140 analyzes the relevant insurancecontract/policy/provision and identifies a relevant coverage amountand/or portion (step 1055). Claim processing is initiated (step 1056),and repair recommendations may be optionally provided to the insuredparty (step 1057). Finally, repairs are electronically scheduled (step1058), which optionally includes providing a legally binding commitmentto the repairing party that they will be reimbursed (up to a specifiedamount).

In one embodiment, command generation engine 130 may send additionalcommands to sensors 90 and/or dwelling computing device 300, such as viadwelling computing device 300 and/or directly to sensors 90. Thesecommands may alter the types of measurements being performed, thefrequency of measurements, the speed/frequency in which information iscommunicated from sensors 90, and/or any other settings. Subsequent toadditional commands being sent to detection devices 90, detectiondevices 90 and/or dwelling computing device 300 execute and/or performthe additional commands and send additional information to managementmodule 105. The additional information may be analyzed independent ofthe previously received information, and/or it may be analyzed and/orcorrelated with the previously received information.

Policy Term Adjustments

FIG. 9 shows, in the form of a flow chart (process 1060), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 9 , it is noted that the flow diagram shown thereinare described, by way of example, with reference to components shown inFIGS. 1-2 , although these operational steps may be carried out in anysystem and are not limited to the scenario shown in the aforementionedfigures. Additionally, the flow diagrams in FIG. 9 shows an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams can be performed in any order, or in anycombination or sub-combination.

With reference to FIG. 9 , starting at step 1061, detection devices,such as sensors 90, are installed at a property, such as a structure,covered by the insurance policy. In one embodiment, sensors 90 may havebeen previously installed for other reasons (e.g., security cameras) andlater re-configured to integrate with system 100. In another embodiment,sensors 90 are installed for at least the reason of integrating with andworking with system 100. In still another embodiment, sensors 90 includea combination of pre-installed sensors 90 and newly-installed sensors90.

Subsequently, information is gathered by from sensors 90 (step 1062) andreceived at management module (step 1063). As discussed above,information may be sent from sensors 90 to dwelling computing device300, and subsequently to management module 105. In another embodiment,dwelling computing device 300 is not installed onsite and sensors 90communicate directly to management module 105. In yet anotherembodiment, dwelling computing device 300 is installed onsite, andsensors 90 communicate directly to management module 105, throughdwelling computing device, and/or a combination thereof.

Information is analyzed by management module 105 (step 1064), such as bydata engine and/or policy engine 140. In one embodiment, data engine 120considers the data and identifies prospective terms of a warranty policyand/or an insurance policy.

Information may also be analyzed by management module 105 to determine avalue of one or more structures (step 1066) and/or one or more items(step 1065), such as appliances, that may be in and around the one ormore structures.

Score-Based Adjustments

It is contemplated herein that the insurance policy terms may be basedon a score calculated from the informatics, the terms may be based on anaverage of scores that were calculated from the informatics, or theterms may be directly based on the informatics.

FIG. 10 shows, in the form of a flow chart (process 1070), exemplaryoperational steps of utilizing system 100. Before turning todescriptions of FIG. 10 , it is noted that the flow diagram showntherein are described, by way of example, with reference to componentsshown in FIGS. 1-2 , although these operational steps may be carried outin any system and are not limited to the scenario shown in theaforementioned figures. Additionally, the flow diagrams in FIG. 10 showsan example in which operational steps are carried out in a particularorder, as indicated by the lines connecting the blocks, but the varioussteps shown in these diagrams can be performed in any order, or in anycombination or sub-combination.

With reference to FIG. 10 , starting at step 1071, a property insurancepolicy is initiated and detection devices are installed at a propertyand/or on a vehicle. This policy may be stored in memory 340, such asdatabase 346. In one embodiment, policy engine 140 has access to thepolicy, such as to the terms of the policy (e.g., premium, deductible,coverage amount, coverage type).

In one embodiment, sensors 90 may have been previously installed forother reasons (e.g., security cameras) and later re-configured tointegrate with system 100. In another embodiment, sensors 90 areinstalled for at least the reason of integrating with and working withsystem 100. In still another embodiment, sensors 90 include acombination of pre-installed sensors 90 and newly-installed sensors 90.

Subsequently, information is gathered and received from detectiondevices 90 (step 1072). As discussed above, information may be sent fromsensors 90 to dwelling computing device 300, and subsequently tomanagement module 105. In another embodiment, dwelling computing device300 is not installed onsite and sensors 90 communicate directly tomanagement module 105. In yet another embodiment, dwelling computingdevice 300 is installed onsite, and sensors 90 communicate directly tomanagement module 105, through dwelling computing device, and/or acombination thereof.

Based on analysis of the informatics, one or more scores may begenerated (step 1073). In one embodiment, a plurality of scores may beaveraged together to generate a single score, and the average score maybe weighted. For example certain characteristics (e.g., workingcondition) may be weighted more heavily than other characteristics(e.g., cleanliness).

Based on the scores, or in some embodiments based on the informaticsdirectly, insurance policy terms are generated, configured and/orreconfigured (step 1074). In one embodiment, a base insurance policy isgenerated, and the score and/or informatics results in adjusted termsfor that insurance policy. In one example, a default home insurancepolicy may be a premium of $3.50 for every $1,000.00 of coverage.However, if the score(s) and/or informatics are positive, than the ratemay be decreased (e.g., $0.50 less per $1000 of coverage) and/or thedeductible amount may be decreased. In another example, certaininformatics may inform certain terms (e.g., the score/informaticsrelated to working condition affects the premium rate, whereas thecleanliness affects the deductible amount). Although certain embodimentsare described herein, the permutations thereof as would be recognized bythose skilled in the art are also contemplated herein.

The policy terms may be sent to the customer (step 1075), and a responsethereto may be received (step 1076). If the response was positive, thenthe newly-insured will be enrolled in the policy terms generated bysystem 100 (step 1077).

In one embodiment, information received at management module 105 isimmediately analyzed and then discarded. In another embodiment theinformation is analyzed and stored.

In one embodiment, information received at management module 105 isimmediately analyzed and then discarded. In another embodiment theinformation is analyzed and stored temporarily. In yet anotherembodiment, the information is stored for later analysis. And in stillanother embodiment, the information is stored via anotherdevice/module/engine.

The term “module”/“engine” is used herein to denote a functionaloperation that may be embodied either as a stand-alone component or asan integrated configuration of a plurality of subordinate components.Thus, “modules”/“engines” may be implemented as a single module or as aplurality of modules that operate in cooperation with one another.Moreover, although “modules”/“engines” may be described herein as beingimplemented as software, they could be implemented in any of hardware(e.g. electronic circuitry), firmware, software, or a combinationthereof.

With certain illustrated embodiments described above, it is to beappreciated that various non-limiting embodiments described herein maybe used separately, combined or selectively combined for specificapplications. Further, some of the various features of the abovenon-limiting embodiments may be used without the corresponding use ofother described features. The foregoing description should therefore beconsidered as merely illustrative of the principles, teachings andexemplary embodiments of this disclosure, and not in limitation thereof.

It is to be understood that the above-described arrangements are onlyillustrative of the application of the principles of the illustratedembodiments. Numerous modifications and alternative arrangements may bedevised by those skilled in the art without departing from the scope ofthe illustrated embodiments, and the appended claims are intended tocover such modifications and arrangements.

FIGS. 11, 12A, and 12B are intended to provide a brief, generaldescription of an illustrative and/or suitable exemplary environment inwhich embodiments may be implemented. FIGS. 11, 12A, and 12B areexemplary of a suitable environment and is not intended to suggest anylimitation as to the structure, scope of use, or functionality of anembodiment of the present disclosure. A particular environment shouldnot be interpreted as having any dependency or requirement relating toany one or combination of components illustrated in an exemplaryoperating environment. For example, in certain instances, one or moreelements of an environment may be deemed not necessary and omitted. Inother instances, one or more other elements may be deemed necessary andadded.

It is to be understood a communication network 2000 is a geographicallydistributed collection of nodes interconnected by communication linksand segments for transporting data between end nodes, such as personalcomputers, work stations, smart phone devices, tablets, televisions,sensors and or other devices such as automobiles, etc. Many types ofnetworks are available, with the types ranging from local area networks(LANs) to wide area networks (WANs). LANs typically connect the nodesover dedicated private communications links located in the same generalphysical location, such as a dwelling 2200 or campus. WANs, on the otherhand, typically connect geographically dispersed nodes overlong-distance communications links, such as common carrier telephonelines, optical light paths, synchronous optical networks (SONET),synchronous digital hierarchy (SDH) links, or Powerline Communications(PLC), and others.

FIG. 11 is a schematic block diagram of an example communication network2000 illustratively comprising nodes/devices 2001-2016 (e.g., sensors2004, client computing devices 2006, routers/switches 2007, smart phonedevices 2008, servers 2012, and the like) interconnected by variousmethods of communication. For instance, the links 2010 may be wiredlinks or may comprise a wireless communication medium, where certainnodes are in communication with other nodes, e.g., based on distance,signal strength, current operational status, location, etc. Moreover,each of the devices can communicate data packets (or frames) with otherdevices using predefined network communication protocols as will beappreciated by those skilled in the art, such as various wired protocolsand wireless protocols etc., where appropriate. In this context, aprotocol consists of a set of rules defining how the nodes interact witheach other. Those skilled in the art will understand that any number ofnodes, devices, links, etc. may be used in the computer network, andthat the view shown herein is for simplicity. Also, while theembodiments are shown herein with reference to a general network cloud,the description herein is not so limited, and may be applied to networksthat are hardwired.

As will be appreciated by one skilled in the art, aspects of the presentdisclosure may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present disclosure may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present disclosure may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present disclosure are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of thedisclosure. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

FIG. 12A is a schematic block diagram of an example network-computingdevice 2030 (e.g., one of network devices 2002-2016) that may be used(or components thereof) with one or more embodiments described herein,e.g., as one of the nodes shown in the network 2000. Device 2030 maycomprise one or more network interfaces 2032, at least one processor2031, and a memory 2036 interconnected by a system bus 2044.

The network interface(s) 2032 contain the mechanical, electrical, andsignaling circuitry for controlling operation of device 2030 and caninclude a media access controller (MAC) 2034, which can communicate datato/from network 2000 using a variety of different communicationprotocols.

Memory 2036 preferably comprises a plurality of storage locations thatare addressable by the processor 2031, MAC 2034 and the networkinterfaces 2032 for storing software programs and data structuresassociated with the embodiments described herein. Note that certainembodiments of device 2030 may have limited memory or no memory (e.g.,no memory for storage other than for programs/processes operating on thedevice and associated caches). The processor 2031 may comprise hardwareelements or hardware logic adapted to execute the software programs andmanipulate the data structures 2042. An operating system 2038, portionsof which are typically resident in memory 2036 and executed by theprocessor and/or network interfaces 2032 (i.e., via MAC 2034),functionally organizes the device by, inter alia, invoking operations insupport of software processes 2040 and/or services executing on thedevice (2002-2016). These software processes and/or services arepreferably used in correlation with the data analysis component 2262 ofFIG. 4 , as described herein. Note that such process/service 2040 may becentralized in memory 2036, or alternatively, such process/service canbe employed within the network interfaces 2032. Further, power supply2046 may supply power to the device 2030.

It will be apparent to those skilled in the art that other processor andmemory types, including various computer-readable media, may be used tostore and execute program instructions pertaining to the techniquesdescribed herein. Also, while the description illustrates variousprocesses, it is expressly contemplated that various processes may beembodied as modules configured to operate in accordance with thetechniques herein (e.g., according to the functionality of a similarprocess). Further, while the processes have been shown separately, thoseskilled in the art will appreciate that processes may be routines ormodules within other processes. Illustratively, the techniques describedwherein may be performed by hardware, software, and/or firmware, such asin accordance with process 2040, which may contain computer executableinstructions executed by the processor 2031 (and/or MAC 2034) to performfunctions relating to the techniques described herein.

In the description that follows, certain embodiments may be describedwith reference to acts and symbolic representations of operations thatare performed by one or more computing devices (2002-2016), such as thecomputing system 2030 of FIG. 12A. As such, it will be understood thatsuch acts and operations, which are at times referred to as beingcomputer-executed, include the manipulation by the processor of thecomputer of electrical signals representing data in a structured form.This manipulation transforms the data or maintains them at locations inthe memory system of the computer, which reconfigures or otherwisealters the operation of the computer in a manner understood by thoseskilled in the art. The data structures in which data is maintained arephysical locations of the memory that have particular properties definedby the format of the data. However, while an embodiment is beingdescribed in the foregoing context, it is not meant to be limiting asthose of skill in the art will appreciate that the acts and operationsdescribed hereinafter may also be implemented in hardware.

It is to be further appreciated, embodiments may be implemented withnumerous other general-purpose or special-purpose computing devices andcomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and configurations that may be suitablefor use with an embodiment include, but are not limited to, personalcomputers, handheld or laptop devices, personal digital assistants,tablet devices, smart phone devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network, sensors, minicomputers, server computers, gameserver computers, web server computers, mainframe computers, anddistributed computing environments that include any of the above systemsor devices. Embodiments may be described in a general context ofcomputer-executable instructions, such as program modules, beingexecuted by a computer. Generally, program modules include routines,programs, objects, components, data structures, etc., that performparticular tasks or implement particular abstract data types. Anembodiment may also be practiced in a distributed computing environmentwhere tasks are performed by remote processing devices that are linkedthrough a communications network. In a distributed computingenvironment, program modules may be located in both local and remotecomputer storage media including memory storage devices.

As explained above, in different embodiments these various devices beconfigured to communicate with each other in any suitable way, such as,for example, via communication network 2000. Device 2030 is only oneexample of a suitable system and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of thedisclosure described herein. Regardless, computing device 2030 iscapable of being implemented and/or performing any of the functionalityset forth herein.

Computing device 2030 is operational with numerous other general purposeor special purpose computing system environments or configurations.Examples of well-known computing systems, environments, and/orconfigurations that may be suitable for use with computing device 2030include, but are not limited to, personal computer systems, servercomputer systems, thin clients, thick clients, hand-held or laptopdevices, multiprocessor systems, microprocessor-based systems, set topboxes, programmable consumer electronics, network PCs, minicomputersystems, mainframe computer systems, and distributed data processingenvironments that include any of the above systems or devices, and thelike.

Computing device 2030 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computing device 2030 may be practiced in distributed dataprocessing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed data processing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

Device 2030 is shown in FIG. 12B in the form of a general-purposecomputing device 2030. The components of device 2030 may include, butare not limited to, one or more processors or processing units 2062, asystem memory 2072, and a bus 2064 that couples various systemcomponents including system memory 2072 to processor 2062.

Bus 2064 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, andlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnect (PCI) bus.

Computing device 2030 typically includes a variety of computer systemreadable media. Such media may be any available media that is accessibleby device 200, and it includes both volatile and non-volatile media,removable and non-removable media.

System memory 2072 can include computer system readable media in theform of volatile memory, such as random access memory (RAM) 2074 and/orcache memory 232. Computing device 2030 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 2078 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 2064 by one or more datamedia interfaces. As will be further depicted and described below,memory 2072 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the disclosure.

Program/utility 2080, having a set (at least one) of program modules2082, such as dwelling analyzer module 2212 and appliance analyzermodule 2214 described below, may be stored in memory 2072 by way ofexample, and not limitation, as well as an operating system, one or moreapplication programs, other program modules, and program data. Each ofthe operating system, one or more application programs, other programmodules, and program data or some combination thereof, may include animplementation of a networking environment. Program modules 2082generally carry out the functions and/or methodologies of embodiments ofthe disclosure as described herein.

Device 2030 may also communicate with one or more external devices 2060such as a keyboard, a pointing device, a display 2070, etc.; one or moredevices that enable a user to interact with computing device 200; and/orany devices (e.g., network card, modem, etc.) that enable computingdevice 2030 to communicate with one or more other computing devices.Such communication can occur via Input/Output (I/O) interfaces 2068.Still yet, device 2030 can communicate with one or more networks such asa local area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 2066. Asdepicted, network adapter 2066 communicates with the other components ofcomputing device 2030 via bus 2064. It should be understood thatalthough not shown, other hardware and/or software components could beused in conjunction with device 200. Examples, include, but are notlimited to: microcode, device drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems, etc.

With the exemplary communication network 2000 (FIG. 11 ) and computingdevice 2030 (FIGS. 12A and 12B) being generally shown and discussedabove, description of certain illustrated embodiments of the presentdisclosure will now be provided. With reference now to FIG. 3 , shown isan example of a dwelling 2200, which is to be understood to be any typeof dwelling structure (e.g., residential, commercial, retail, municipal,etc.) in which the capture and analysis of sensor data (2004) is usefulfor the reasons at least described below. Dwelling 2200 preferablyincludes a computing device 2006 for capturing data from a plural ofsensors 2004 which capture data regarding various aspects of dwelling2200, as further described below. It is to be understood dwellingcomputing device 2006 may be located in any location, and its positionis not limited to any one particular location.

Computing device 2006 is preferably configured and operational toreceive (capture) data from various sensors 2004 regarding certainaspects (including functional and operational) of dwelling 2200(described further below) and transmit captured data to a remote server206, preferably via network 2000. It is noted device 2006 may performanalytics regarding the captured sensor data for dwelling 2200, and/orthe remote server 206, preferably located or controlled by an insurancecompany/carrier, may perform such analytics, as also further describedbelow. It is also to be understood in other embodiments, data fromsensors 2004 may be transmitted directly to remote server 2012, vianetwork 2000, thus either obviating the need for dwelling computingdevice 2006 or mitigating its functionality to capture data from allsensors 2004.

In the illustrated embodiment of FIG. 13 , dwelling-computing device2006 is shown coupled to various below described sensor types 2004.Although various sensor types 2004 are described below and shown in FIG.13 , the sensor types described and shown herein are not intended to beexhaustive as the present disclosure may encompass any type of known orunknown sensor type which facilitates the purposes and objectives of thecertain illustrated embodiments described herein. Exemplary sensor typesinclude (but are not limited to):

Temperature sensor-configured and operational to preferably detect thetemperature present at the dwelling 2200. For example, the temperaturemay rise and fall with the change of seasons and/or the time of day.Moreover, in the event of a fire, the temperature present at thedwelling 2200 may rise quickly-possibly to a level of extreme high heat.The temperature sensor may make use of probes placed at variouslocations in and around the dwelling 2200, in order to collect arepresentative profile of the temperature present at the dwelling 2200.These probes may be connected to device 2006 by wire, or by a wirelesstechnology. For example, if device 2006 is positioned in the attic ofthe dwelling 2200, the temperature may be higher than the generaltemperature present in the dwelling. Thus, probes placed at variouslocations (e.g., in the basement, on the various levels of a multi-leveldwelling 2200, in different rooms that receive different amounts of sun,etc.), in order to obtain an accurate picture of the temperature presentat the dwelling. Moreover, device 2006 may record both the indoor andoutdoor temperature present at the dwelling 2200. For example, dataabout the indoor temperature, the outdoor temperature, and/or thedifferential between indoor and outdoor temperatures, may be used aspart of some analysis model, and thus all of the different values couldbe stored. Device 2006 may store an abstract representation oftemperature (e.g., the average indoor temperature, as collected at allof the probes), or may store each temperature reading individually sothat the individual readings may be provided as input to an analysismodel.

Humidity sensor-configured and operational to preferably detect thehumidity present at the dwelling 2200. Humidity sensor may comprise thehumidity-detection hardware, or may employ one or more remote probes,which may be located inside and/or outside the dwelling 2200. Humidityreadings from one or more locations inside and/or outside the dwellingcould thus be recorded by device 2006.

Water pressure sensor—configured and operational to preferably monitorwater pressure in the plumbing system in the dwelling 2200. Waterpressure sensor may have one or more probes attached to variouslocations of the dwelling's 2200 plumbing, and thus device 2006 mayrecord the pressure present in the plumbing, and/or any changes in thatpressure. For example, plumbing systems may be designed to withstand acertain amount of pressure, and if the pressure rises above that amount,the plumbing system may be at risk for leaking, bursting, or otherfailure. Thus, device 2006 may record the water pressure (and waterflow) that is present in the plumbing system at various points in time.

Water flow sensor—configured and operational to preferably monitor waterflow rate in the plumbing system in the dwelling 2200. Water flow sensormay have one or more probes attached to various locations of thedwelling's 300 plumbing, such as faucets, showerheads and appliances,and thus water flow sensor may measure and/or record the amount of waterflowing through the dwelling's 300 water supply system. Thus, device 103may record the water flow that is present in the plumbing system atvarious points in time. An analysis model could use the informationabout water flow in various ways such as rating the home insurance,tracking water consumption, or providing advice and guidance. Thereadings of the amount of water used at dwelling 2200 can be used toanalyze and forecast an expected water bill. This can also be used forbudgeting and finance management because a history of water usage at thedwelling 2200 or certain appliances can be measured and displayed to thehomeowner or insurance company. These readings and usage can be providedto the homeowner so that he can budget X amount of money each month forthe water bill. Also, the homeowner or insurer can track water use anddetermine based upon the rate of energy consumption that the homeowneris on a pace to use more or less water use than is budgeted. If thehomeowner is on pace to use more water than is budgeted the insurancecompany can provide advice and guidance on how the homeowner can reducewater use. If the homeowner is on pace to use less water than isbudgeted the insurance company can help the homeowner in moving theunspent portion of the budget amount to a savings device like a CD ormoney market.

Water Detection sensor—configured and operations to preferably monitorwater leaks or moisture in the plumbing system in the dwelling 2200.Water detection sensor may have one or more probes/sensors attached tovarious locations of the dwelling's 2200 plumbing, and thus device 2006may record a potential water leak or area of moisture buildup in thehome.

Wind speed sensor—configured and operational to record the wind speedpresent at the dwelling 2200. For example, one or more wind sensors maybe placed outside the dwelling 2200, and the wind speed and/or directionmay be recorded at various points in time. Device 2006 may record thesewind speed and/or wind direction readings. The wind speed may be used byan analysis model for various purposes. For example, the wind speedand/or direction at specific points in time during a hurricane may helpto understand how well the dwelling 2200 withstood a hurricane or topredict emergence of a dangerous situation. If the wind speed rises to acertain level just before a house is destroyed in a hurricane, this factmay be used to estimate the amount of wind that the house couldwithstand. Or, as another example, measurements of wind speed and/ordirection taken at a time other than when a hurricane is occurring couldbe used to forecast the risk that a house will suffer damage. Evennon-hurricane-force winds can cause damage to a dwelling 2200, and aninsurer might be interested to know if the prevailing wind speed in thevicinity of the dwelling 2200 is increasing or decreasing. Thisinformation could be used to plan for future losses and/or to makefuture underwriting decisions.

Motion sensor—configured and operational to sense motion in the dwelling2200 to which device 2006 is attached. Typically, dwelling's 2200 do notmove significantly, except in the event of a catastrophe. Motion mayindicate that the dwelling 2200 is sliding down a hill (e.g., in theevent of an extreme flood or mudslide), or is experiencing a measurableearthquake. Moreover, in the event of a complete collapsed, it is likelythat device 2006 (or a motion sensor probe used by device 2006) willmove, and thus such motion could be used to identify the moment at whichthe dwelling 2200 collapsed. Motion sensor also encompasses the type todetect movement inside of a dwelling for alarm purposes and/or todetermine the habits/trends of dwelling inhabitants. An analysis modelcould use the information about motion in various ways. For example, ifan abrupt motion indicates that the dwelling 2200 collapsed at a certainpoint in time, then data such as temperature, wind speed, etc., could beused to determine what was happening (e.g., fire, high winds, etc.) atthe time of the collapse. A motion sensor may further include earthsensors for detecting sink holes and earth movement. This informationmay be used to understand the cause of the collapse. Or, as anotherexample, the information could be used to assess an insurance claim(e.g., an insurer's liability for wind damage might be different thanfor fire damage, and thus knowing what was happening at the moment ofthe collapse might be used to determine what, if any, settlement is dueto an insured). Or, as another example, a motion sensor may beconfigured and operational to determine how often a kitchen is usedand/or what time the dwelling inhabitants sleep, leave and return fromwork, etc.

Electrical system sensor/analyzer configured and operational to assessthe condition of the dwelling's 2200 electrical system. For example,potentiometers may be connected to various points in the dwelling's 2200electrical system to measure voltage. Readings from the potentiometerscould be used to determine if the voltage is persistently too high, ortoo low, or if the voltage frequently drops and/or spikes. Suchconditions may suggest that the dwelling 2200 is it at risk for fire.Other types of electrical measurements could be taken, such as readingsof current flowing through the electrical system. Still other types ofelectrical measurements that could be determined include how energy isused and at what times of day it is used, etc. Any type of data aboutthe dwelling's 2200 electrical system could be captured by device 2006.An analysis model could use the information about electrical energy invarious ways. Additionally, the home's energy usage could be identifiedand calculated. This energy consumption could then be tied in to thehomeowner's budget and act as barometer for how well they are on trackto meet their goal.

Positional sensor configured and operational to record the position ofdevice 2006. For example, the positional sensor may be, or may comprise,a Global Positioning System (GPS) receiver, which may allow the positionof device 2006 to be determined. Or, as another example, positionalsensor may use triangulation technology that communicates with fixedpoints (such as wireless communication towers) to determine itsposition. While a dwelling 2200 normally does not move, positionalsensor may allow device 2006 to be recovered in the event of acatastrophe. For example, if a dwelling 2200 explodes, or is otherwisecatastrophically damaged, device 2006 may be propelled to an unknownlocation. Positional sensor may indicate the geographical area of adwelling 2200 which an analysis model could use in various ways.Positional sensor may record the position of device 2006, which device2006 could communicate to an external source, thereby allowing device2006 to be found.

Structural sensor—configured and operational to preferably detectvarious structural conditions relating to dwelling 2200. A structuralsensor may comprise detection hardware, or may employ one or more remoteprobes, which may be located inside and/or outside the dwelling 2200.Conditions recorded by structural sensor 300 may include (but are notlimited to) the condition of the wall structure, floor structure,ceiling structure and roof structure of dwelling 2200, which may beachieved via: load bearing detectors; components which measure the slopeof a floor/wall/ceiling; carpet conditions (e.g., via nano sensors) orany another components functional to detect such conditions. Structuralreadings from one or more locations inside and/or outside the dwelling2200 could thus be recorded by device 2006 and used by an analysis modelin various ways.

Environmental Sensor—configured and operational to preferably detectvarious environmental conditions relating to dwelling 2200. Anenvironmental sensor may comprise detection hardware, or may employ oneor more remote probes, which may be located inside and/or outside thedwelling 2200. Conditions recorded by an environmental sensor 300 mayinclude (but are not limited to) the air quality present in dwelling2200, the presence of mold/bacteria/algae/lead paint or any contaminantadverse to human health (whether airborne or attached to a portion ofthe structure of dwelling 2200). Such environmental readings from one ormore locations inside and/or outside the dwelling 2200 could thus berecorded by device 2006 and used by an analysis model in various ways.

Appliance Sensor—configured and operational to preferably detect variousoperating parameters relating to appliances within a dwelling 2200.Examples of appliances include (but are not limited to) all kitchenappliances (e.g., refrigerator, freezer, stove, cooktop, oven, grill,dishwasher, etc.); HVAC components (air conditioner, heating system, airhandlers, humidifiers/de-humidifiers, etc.), water purification system,media entertainment system (e.g., televisions), networking components(routers, switches, extenders, etc.), electrical generator system, poolfiltration and heating system, garage door openers, sump pump and waterwell system, septic tank system, garage door opener, etc. An appliancesensor may comprise detection hardware, or may employ one or more remoteprobes, which may be located inside and/or outside the dwelling 2200functional to detect certain operating parameters of appliances.Operating parameters detected by an appliance sensor 300 may include(but are not limited to): the operating efficiency of an appliance(energy usage, output performance); the time an appliance operates; theage of an appliance; maintenance needs of an appliance (e.g., change afilter component or schedule a periodic examination/tune-up); and repairneeds of an appliance (which may also include the identification ofparts needed). Such appliance readings from one or more dwellingappliances could thus be recorded by device 2006 and used by an analysismodel in various ways.

Optical Recognition Sensor—configured and operational to recognizeobjects within a dwelling 2200 using optical characteristics.

Activity Monitoring Sensor—configured and operational to obtaininformation related to physical activity of the policyholder associatedwith a dwelling 2200. Three general categories of sensors can be usedfor measuring physical activity: movement sensors, physiologicalsensors, and contextual sensors. Many movement sensors can be used tomeasure human physical activities, including electromechanical switches(for heel strike detections), mercury switches, pedometers,inclinometers, gyroscopes and goniometers (for angles or postures), andaccelerometers. Collectively, accelerometers are well-suited formeasuring intensity of movements, thus are predominately used forassessing outcomes, such as overall physical activity levels andestimated energy expenditure. Examples of physiologic sensors mayinclude (but are not limited to) heart rate, gas exchange (02 and C02 inbreath and in blood), blood pressure, temperature (skin and core body),heat flux, sweating (galvanic skin response), blood chemistry(continuous glucose), electromyogram (electrical activity of muscle),and breathing frequency and volume. Some additional physiologic sensorsmay be useful for measuring specific components of physical activitythat could not be achieved using movement sensors, such as using anelectromyogram to assess skeletal muscle function and implantablesensors to detect blood glucose levels. Local contextual sensors can beused to answer questions about physical activity within structures, suchas work-based activity patterns or movement patterns within the dwelling2200.

With exemplary sensors 2004 identified and briefly described above, andas will be further discussed below, it is to be generally understoodsensors 2004 preferably record certain data parameters relating toproducts and services provided by an insurance carrier, to enhance lossmitigation (e.g., push data in real-time from dwelling 2200 formaximizing preventable losses); determine dwelling damage; determinerisk situations present; provide alarms/alerts; determine maintenanceand repair needs; determine age and condition of a dwelling; determinehabits and trends of dwelling 2200 inhabitants; and determine status ofdwelling 2200 repairs and/or remodeling efforts (e.g., determine whereand what type of work is being performed in a dwelling); and other valueadded services such as those described below.

It is to be understood and appreciated the aforementioned sensors 2004may be configured as wired and wireless types integrated in a networkedenvironment (e.g., WAN, LAN, Wi-Fi, 802.11X, 30, LTE, etc.), which mayalso have an associated IP address. It is to be further appreciated thesensors 2004 may consist of internal sensors located within thestructure of dwelling 2200; external sensors located external of thestructure of dwelling 2200; sound sensors for detecting ambient noise(e.g., for detecting termite and rodent activity, glass breakage,intruders, etc.); camera sensors such as those consisting of camerastandalone devices, or by integrating into existing camera devices in adwelling 2200. It is additionally to be understood and appreciated thatsensors 2004 can be networked into a central computer hub (e.g., device2006) in a dwelling to aggregate collected sensor data packets.Aggregated data packets can be analyzed in either a dwelling computersystem (e.g., device 2006) or via an external computer environment(e.g., server 206). Additionally, it is to be understood data packetscollected from sensors 2004 can be aggregated in dwelling computingdevice 2006 and send as an aggregated packet to server 2012 forsubsequent analysis whereby data packets may transmitted at prescribedtime intervals (e.g., a benefit is to reduce cellular charges in thatsome dwellings 2200 may not have Internet access or cellular service isbackup when dwelling Internet service is nonfunctioning).

In accordance with an illustrated embodiment, in addition to theaforementioned the sensors 2004 being utilized relative to dwelling2200, dwelling computing device 2006 may additionally be coupled to aclock 2204 which may keep track of time for device 2006, therebyallowing a given item of data to be associated with the time at whichthe data was captured. For example, device 2006 may recurrently capturereadings of temperature, wind speed, humidity, appliance operatingtimes, etc., and may timestamp each reading. The time at which thereadings are taken may be used to reconstruct events or for otheranalytic purposes, such as those described below. For example, thetimestamps on wind speed readings taken during a hurricane may allow itto be determined, after the hurricane has occurred, how quickly the windspeed rose in the vicinity of the dwelling 2200.

A storage component 2206 may further be provided and utilized to storedata readings and/or timestamps in device 2006. For example, storagecomponent 2206 may comprise, or may otherwise make use of, magnetic oroptical disks, volatile random-access memory, non-volatile random-accessmemory, or any other type of storage device. There may be sufficientdata storage capacity to store several hours or several days-worth ofreadings. For example, the severe part of a hurricane might last forhalf a day, a full day, or several days. Further, in another example,there might be various plumbing issues which may affect the waterpressure in a plumbing system to be low. Storage component 2206 mighthave sufficient storage capacity to allow twelve or more hours ofreadings to be stored, thereby allowing forensic reconstruction of howthe hurricane affected the dwelling 2200 during the full time that thedwelling 2200 was experiencing the hurricane's impact and/or allow, forexample, five days of readings to be stored, such that the cause of thelow water pressure may be diagnosed.

A communication component 2208 may further be provided and utilized tocommunicate recorded information from dwelling computing device 2006 toan external location, such as computer server 206, which may beassociated with an insurance carrier. Communication component 2208 maybe, or may comprise, a network communication card such as an Ethernetcard, a Wi-Fi card, or any other communication mechanism. However,communication component 2208 could take any form and is not limited tothese examples. Communication component 2208 might encrypt data that itcommunicates, in order to protect the security and/or privacy of thedata. Communication component may communicate data recorded by device2006 (e.g., data stored in storage component 2206) to an externallocation, such as server 2012. For example, server 2012 may be operatedby an insurance company, and may collect data from dwelling computingdevice 2006 in order to learn about risks and needs and other analyticsrelative dwelling 2200 in which device 2006 located. Communicationcomponent 2208 may initiate communication sessions with server 2012. Or,as another example, server 2012 may contact device 2006, throughcommunication component 2208, in order to receive data that has beenstored by device 2006. Additionally, data from sensors 2004, clock 2204and/or storage component 2206 may be communicated directly to server2012, via network 2000, thus obviating or mitigating the need fordwelling computing device 2006.

In the example of FIG. 13 , communication component 324, as being partof, or used by, dwelling computing device 2006) communicates data toserver 2012. Server 2012 may comprise, or otherwise may cooperate with,a data analysis module 2210, which may analyze data in some manner. Dataanalysis module 2210 may comprise various types of sub-modules, such asdwelling analyzer 2212, appliance analyzer 2214, policy analyzer 2216,data analyzer 2218, maintenance manager 2220, credit analyzer 2222, andcomposite risk analyzer 2224. In general, dwelling analyzer 2212 mayperform an analysis of collected data regarding various aspects ofdwelling 2200, such as data that used to determine age and condition ofdwelling 2200; determine maintenance and repair needs for dwelling 2200and the like. Appliance analyzer 2214 may perform an analysis ofcollected data regarding various appliances located in or arounddwelling 2200, such as their age, operating parameters,maintenance/repair issues, and the like. Dwelling analyzer 2212 andappliance analyzer 2214 may overlap somewhat in terms of the techniquesthey employ—e.g., both of these sub-modules may analyze facts such asroom temperature, humidity, etc., and attempt to draw some conclusionsbased on whether and/or how these facts have changed over time.

In general, maintenance manager 2220 may perform an analysis ofmaintenance profile generated by dwelling analyzer 306 and may performan analysis of an insurance policy associated with the dwelling 2200.Moreover, maintenance manager 2220 may initiate a potential insuranceclaim related to one or more identified repair and/or maintenance needs.Server 106 may further comprise, or otherwise may cooperate with, aclaim system repository 310, which may store various claim related dataand information.

FIG. 13 illustrates dwelling 2200 appliances from which sensor data iscaptured for subsequent analysis in accordance with an illustratedembodiment. Computing device 2006 elements such as clock 2204, storagecomponent 2206 and communication component 2208, as well as sub-modulesof data analysis module 2210 have already been described with respect toFIG. 13 . In addition to those elements already described,illustratively, a plurality of appliances are depicted in FIG. 13 .Examples of appliances include (but are not limited to) all kitchenappliances (e.g., refrigerator 2230, freezer, stove, cooktop, oven,grill, dishwasher, etc.); HVAC components 2232 (air conditioner, heatingsystem, air handlers, humidifiers/de-humidifiers, etc.), waterpurification system 2234, media entertainment system 2236 (e.g.,televisions), networking components 2238 (routers, switches, extenders,etc.), electrical generator system, and the like. In many of theembodiments, appliances 2230-2238 have a computer based architecture ora controller that enables communication of data concerning theelectronic appliance. It is to be understood dwelling appliances2230-2238 may be located in any location inside or outside of dwelling2200, and their positions are not limited to the example depicted inFIG. 13 . In addition, a plurality of appliance sensors 2240 may beattached to and/or operatively connected to controllers of dwellingappliances 2230-2238.

Each of the appliance sensors 2240 may be configured and operational topreferably detect various operating parameters relating to appliances2230-2238 within or outside the dwelling 2200. An appliance sensor maycomprise detection hardware, or may employ one or more remote probes,which may be located inside and/or outside the dwelling 2200, functionalto detect certain operating parameters of appliances 2230-2238.Operating parameters detected by an appliance sensor 2240 may include(but are not limited to): the operating efficiency of an appliance(energy usage, output performance); the time an appliance operates, theage of an appliance. Such appliance readings from one or more dwellingappliances 2230-2238 could thus be recorded by device 1 03 and used byan appliance analyzer 2214 in various ways. It is additionally to beunderstood and appreciated that appliance sensors 2240 can also benetworked into a central computer hub (e.g., device 2006) in a dwellingto aggregate collected sensor data packets. Dwelling computing device2006 may communicate its data to server 2012.

FIGS. 14 and 15 show, in the form of a flow chart, exemplary operationalsteps of the dwelling analyzer 2212 and policy analyzer 2216,respectively. Before turning to descriptions of FIGS. 14 and 15 , it isnoted that the flow diagram shown therein are described, by way ofexample, with reference to components shown in FIGS. 11-13 , althoughthese operational steps may be carried out in any system and are notlimited to the scenario shown in the aforementioned figures.Additionally, the flow diagrams in FIGS. 14 and 15 show an example inwhich operational steps are carried out in a particular order, asindicated by the lines connecting the blocks, but the various stepsshown in these diagrams can be performed in any order, or in anycombination or sub-combination.

As previously noted, dwelling computing device 2006 may communicate itsdata to server 2012. FIG. 14 shows an example in which server 2012receives such data, and in which the data is used in various ways. Inthe example of FIG. 14 , communication component 2208 (which is shown,in FIG. 13 , as being part of, or used by, dwelling computing device2006) communicates data 2260 to server 2012. Server 2012 may comprise,or otherwise may cooperate with, a data analysis component 2262(preferably utilizing software processes 2040), which may analyze data2260 in some manner (e.g., predictive analytics). Data analysiscomponent 2262 may comprise various types of sub-components, such asforensic analyzer 2264 and prospective analyzer 2268. In general,forensic analyzer 2264 may perform an analysis. For example, in oneembodiment, a post hoc analysis, such as that used to understand thedetails of how a dwelling 2200 was damaged or destroyed during ahurricane, a fire, etc. Moreover, in general, prospective analyzer 2268may analyze data to assess the risk of destruction and/or damage thathas not yet happened; enhance loss mitigation for an insurance carrier(e.g., push data in real-time from dwelling 2200 for maximizingpreventable losses); determine dwelling damage; determine risksituations present; provide alarms/alerts. Additionally and/oralternatively, an analysis may be performed on collected data regardingvarious aspects of the dwelling 2200, such as to determine maintenanceand repair needs for dwelling 2200; determine age and condition of adwelling; determine habits and trends of dwelling 2200 inhabitants; anddetermine status of dwelling 2200 repairs and/or remodeling efforts(e.g., determine where and what type of work is being performed in adwelling); and other value added services such as those described below.Forensic analyzer 2264 and prospective analyzer 2268 may overlapsomewhat in terms of the techniques they employ (e.g., both of thesesub-components may analyze facts such as room temperature, humidity,wind speed, etc., and attempt to draw some conclusions based on whetherand/or how these facts have changed over time).

The analysis performed by data analysis component 2262 may be used tomake various types of decisions and/or enable the provision if certainproducts/services such as those that can be offered by insurance carrierservices 2270. FIG. 14 illustrates exemplary decisions/products/services2272-2296 that may be made based on analysis and predictive analysis,although the specific decisions decisions/products/services 2270 thatare shown do not constitute an exhaustive list. Any type of decision maybe made.

One type of decision that may be made is a claims decision 2272. Forexample, if a claim is made against an insurance policy, whether theclaim is to be paid (or the amount of the claim to be paid) may dependon how a building was damaged or destroyed. Many homeowner's insurancepolicies insure against fire and earthquake differently (e.g., somepolicies cover fire but not earthquake), so if an earthquake strikes anda building is found collapsed and burnt, there are at least twopossibilities as to how the building arrived in its current condition:(1) the building collapsed from the earthquake and then its collapsedremains burnt, or (2) the earthquake started a fire that burnt thebuilding, and the burnt building remains collapsed. If fire is a coveredrisk and earthquake is not, then it may be relevant to determine whether(1) or (2) is what happened, since (2) would be a covered loss event and(1) would not be a covered loss event. Thus, analysis of data from adata recorder may be used to determine how a building was damaged ordestroyed, which may be relevant in determining whether and/or how topay a claim.

Another type of decision that may be made based on data from sensors2004 is a subrogation decision 2274. For example, as thepreviously-described earthquake/fire example shows, the cause of abuilding's damage or destruction may be ambiguous. Whether to pay aclaim is one type of decision that may be made based on how destructionand/or damage occurred, but another decision is whether to subrogate theclaim. For example, property insurance may cover losses by fire andflood, but flood losses may be covered by a government insurance programand may be subrogatable. If a building collapses in a hurricane, it maybe unclear whether the building collapsed from wind or from floodwaters,and yet this distinction may determine whether to subrogate the claim.Data from a data recorder may be used to make such a decision.

Another type of decision that may be made based on data from sensors2004 is an underwriting decision 2276. For example, an insurance companymay collect data about a house, and may use this data to determinewhether to continue insuring that house, or to set the premium forinsuring the house. Or, data about houses in a geographic area may becollected, and the insurance company may use this data to determine thegeneral level of risk in the area. For example, if analysis of the datafrom fifty houses in a particular geographic location shows that averagewind speed has been increasing over the past few years, then theinsurance company may use this information to determine that thelikelihood of losses due to wind damage is increasing, and may makecoverage and/or premium pricing decision accordingly.

Another type of decision that may be made based on data from sensors2004 is a reinsurance decision 2278. As previously discussed, the datamay be used in making underwriting decisions. Along the same lines, aninsurance company may use this data to determine how much re-insuranceto purchase. If analysis of the data from the data recorder indicatesthat the insurance company's expected loss will exceed the company'stolerance for absorbing the losses, then the company may choose topurchase reinsurance. Thus, reinsurance decisions are yet another typeof decision that may be made based on data from a data recorder.

Another type of decision that may be made based on data from sensors2004 is an alert decision 2280. For example, if prospective analysis ofcollected data indicates that a house is at risk for some type of damage(e.g., fire, theft, C02, Radon gas, foundation cracking, due to rottingcaused by high humidity), an alert may be issued to the building ownerin order to encourage the owner to take remedial action.

Another type of decision that may be made based on data from sensors2004 is insurance coverage modification decision 2282. Based on datacollected from sensors 2004 regarding a dwelling 2200, analysis isconducted to determine change recommendations to insuranceproducts/services (that may be either currently existing or non-existingto a policy holder) which may be beneficial to a policy holder in viewof current subscribed insurance products and coverage levels. Forinstance, a homeowner may not have insurance covering a particular typeof event/loss, and based upon collected, and analyzed data from sensors2004 (amongst possible other factors), a recommendation may be providedto a homeowner to subscribe to insurance covering such a particular typeof event/loss. Additionally, a recommendation may be provided toincrease, decrease, or make other adjustments to personal liabilitylimits based upon detected trends and habits determined at least in partby data collected from certain sensors 2004.

Another type of decision that may be made based on data from sensors2004 is maintenance and/or repair decision 2284. Based on data collectedfrom sensors 2004 regarding a dwelling 2200, analysis is conducted todetermine recommendations to make certain repairs (whether immediatelyneeded or preventive in nature) to the structure of a dwelling 2200and/or the dwelling appliances. For instance a hole may have beendetected in the roof of a dwelling 2200 (via one or more sensors 2004)requiring immediate repair, or based upon certain analysis preventivemaintenance is recommended to the roof a dwelling 2200 (e.g., detectionof wind, moisture, improper roof slope line, etc.). Additionally,recommendations may be made with regards to appliances in the dwelling2200. For instance, a recommendation may be made to repair an appliance(e.g., freezer) due to detected performance degradation contingent uponeither it's past operating performance efficiency and/or its operatingperformance falling outside of threshold values prescribed for it by amanufacture. As another example, recommendations may be made to replacean HVAC filter element based upon detection of a dirty filter element ordegradation in HVAC equipment performance likely contributable to adirty filter element.

Another type of decision that may be made based on data from sensors2004 is dwelling operation decision 2286. Based on data collected fromsensors 2004 regarding operation of a dwelling 2200, analysis isconducted to determine recommendations to make certainadjustments/changes regarding operation a dwelling 2200. For instance,sensors 2004 may detect no inhabitants are home during certain hours ofa day, thus adjustments to the HVAC system are recommended. As anotherexample, sensors may detect a dryer is frequently used during peakutility hours thus a recommendation is made by data analysis component2262 to operate the dryer during non-peak hours to gain the benefit oflower electricity rates.

Another type of decision that may be made based on data from sensors2004 is purchase decision 2288. Based on data collected from sensors2004 regarding operation of a dwelling 2200, analysis is conducted todetermine recommendations to purchase new or replacement appliances fora dwelling 2200. For instance, sensors 2004 may detect frequent highhumidity levels in a dwelling 2200 and may thus recommend purchase of ade-humidifier. Additionally, the data analysis component 2262 maydetermine that based on age and operating efficiency of an airconditioning unit for a dwelling 2200, a new unit would be morebeneficial and economical for the owner/operator of a dwelling 2200.

Another type of decision that may be made based on data captured fromsensors 2004 is appliance insurance decision 2290. Based on datacollected from sensors 2004 regarding operating parameters of appliancesin a dwelling 2200, analysis is conducted in component 2262 to determinewhether the provision of appliance warranty/replacement insurance wouldbe beneficial to the owner/operator of the dwelling 2200. The premiumamount for such an insurance product is preferably determined andcontingent upon such factors including operating performance,maintenance history, habits/trends of dwelling inhabitants and applianceage via data captured from various sensors 2004 and other sources.

Another type of decision that may be made based on data captured fromsensors 2004 is policy discount decision 2292. Based on the decision ofan owner/operator of a dwelling 2200 to share data from sensors 2004with an insurance carrier (e.g., insurance carrier server 206), discounton the insurance policy for a dwelling 2200 may be provided. Maintaining(or providing adjustments to) the policy discount may be contingent uponthe adherence of certain conditions, such as maintenance of the dwellingstructure, as determined by data captured from the dwelling sensors2004. As another example, data analysis component 2262 may compile ahome maintenance score (dependent upon sensor data) which is utilized todetermine if it satisfies a threshold score value prescribed by theinsurance carrier to maintain policy discounts contingent uponprescribed maintenance obligations.

Another type of service that the insurance carrier services 2270 mayprovide based on data captured from sensors 2004 is builder notification2294. Based on the data collected from the various sensors 2004 of adwelling 2200, this data may be complied and/or aggregated into acertain format so as to be shared with dwellingbuilders/contractors/designers to improve future build quality/design ofa similar dwelling and/or for soliciting dwelling improvementrecommendations from such builders/contractors/designers.

Still another type of service that the insurance carrier services 270may provide based on data captured from sensors 2004 is automaticinitiation of a claims submission/adjustment process on behalf of apolicy holder for a dwelling 2200. For instance, when data analysiscomponent 2262 detects a claims submission/adjustment has occurredrelative to a dwelling 2200 (e.g., flooded basement) based upon datafrom one or more sensors 2004, the claims submission process isautomatically initiated to expedite the process on behalf of the policyholder for a dwelling 2200, preferably in the absence of any submissionby the policy holder for a dwelling 2200.

With certain services that may be provided by the insurance carrierservices 2270 described above in conjunction with FIG. 14 , it is to beappreciated that all applicable alerts I alarm signals I and othernotifications regarding such services/processes 2272-2296 are to beprovided in all applicable communications formats (e.g., email,telephony, txt, smart phone apps, social media, social media (Twitter,Facebook), etc.). It is to be also understood and appreciated thatinsurance carrier services 2270 (preferably via computer server

206) is configured and operational to integrate with user communicativecomputing devices (e.g., smart phones (via an app), computers, tablets,smart TV's, vehicle communication systems, etc.) for sending such alertsI alarm signals I and other notifications regarding suchservices/processes 2272-2296.

FIG. 15 shows, in the form of a flow chart, an example process 2310 inwhich data may be recorded and used. Before turning to a description ofFIG. 15 , it is noted that the flow diagram shown therein is described,by way of example, with reference to components shown in FIGS. 11-14 ,although this process may be carried out in any system and is notlimited to the scenario shown in FIGS. 11-14 . Additionally, the flowdiagrams in FIG. 15 shows an example in which stages of a process arecarried out in a particular order, as indicated by the lines connectingthe blocks, but the various stages shown in this diagram can beperformed in any order, or in any combination or sub-combination.

At 2312, a dwelling computing device 2006 may be placed in a dwelling.For example, dwelling computing device 2006 may be placed in dwelling2200, as shown in FIG. 13 (although any type or number of dwellingcomputing devices 2006 could be placed in any type of dwelling). At2314, the dwelling computing device 2006 collects data from sensors2004. Mechanism by which the dwelling computing device 2006 may collectsensor data have been previously described in connection with FIG. 13 .

At 2316, contact is made between the dwelling computing device 2006 anda mechanism that collects data from the dwelling computing device 2006.An example of such a mechanism is insurance carrier server 2012 (vianetwork 2000) (shown in FIG. 13 ), although the subject matter herein isnot limited to this example. As previously described, contact betweenthe dwelling computing device 2006 and a server 2012 may be initiatedwhen the server 2012 contacts the dwelling computing device 2006 (at2318), or when the mechanism receives a contact request from thedwelling computing device 2006 (at 2320).

At 2322, following the initial contact between the dwelling computingdevice 2006 and the server 206, server 2012 may receive data from thedwelling computing device 2006. At 2324, the data may be analyzedpreferably in data analysis component 2262. As noted previously inconnection with FIG. 14 , the analysis may include a forensic analysis(at 2326) and/or a prospective analysis (at 2328). At 2330, a decisionmay be made based on the analysis that has been performed. Examples ofsuch decisions, and examples of techniques that may be used in makingsuch decisions, have been described previously in connection with FIG.14 . At 2332, a tangible action may be taken based on the decision thatis made. For example, if prospective analysis indicates that a buildingmay be heading toward damage, an alert could be issued and communicatedto the building's owner, and the owner could take remedial action suchas affecting a physical condition present at the building (e.g.,reducing the temperature and/or humidity level, installing new equipmentin the building, repairing an existing physical condition in thebuilding, etc.).

With reference to process 2350 of FIG. 16 , at 2352, dwelling analyzer2212 preferably collects data from sensors 2004. In an embodiment of thepresent disclosure, this step may involve computing device 2006periodically contacting (via network 1 00), at prescribed timeintervals, data analyzer component 2218 running on server 2012 to sendaccumulated data. In an alternative embodiment, contact between thedwelling computing device 2006 and dwelling analyzer 2212 may beinitiated when the dwelling analyzer 2212 contacts the dwellingcomputing device 2006. Following the initial contact, dwelling analyzer2212 may receive data from the dwelling computing device 2006. It is tobe understood data packets collected from sensors 2004 can be aggregatedin dwelling computing device 2006 and send as an aggregated packet todwelling analyzer 2212 for subsequent analysis.

At 2354, dwelling analyzer 2212 preferably processes the received data.For example, dwelling analyzer 2212 may include a parser configured toparse the aggregated packet and classify the received data based on, forexample, type of sensor employed to collect a particular subset of thereceived data. Dwelling analyzer 2212 may create a data structure foreach classification. This step may further involve identifying a policyholder associated with dwelling 2200 from which the received data iscollected. At 2356, based on data collected from sensors 2004 regardinga dwelling 2200, dwelling analyzer 2212 conducts an analysis todetermine recommendations to make certain immediately needed repairs tothe structure of a dwelling 2200. For instance a hole may have beendetected in the roof of dwelling 2200 (via one or more sensors 2004),requiring immediate repair. As another example, an environmental sensormay have detected a gas leak or any contaminant adverse to human health.As another example, dwelling temperature analysis may have indicated amalfunctioning cooling/heating system. In general, any dwellingcondition that affects the residents' health or safety may be consideredby dwelling analyzer 2212 as requiring an immediate repair. Similarly,at 2358, dwelling analyzer 2212 conducts an analysis to identify certainpreventive repairs to the structure of a dwelling 2200. For example,based upon certain analysis, dwelling analyzer 2212 may recommendpreventive maintenance to the roof a dwelling 2200 (e.g., detection ofwind, moisture, improper roof slope line, etc.). As another example,based upon analysis of a plumbing system, dwelling analyzer 2212 mayhave detected long-term stress on pipes. In order to prevent waterleaks, dwelling analyzer 2212 may recommend reducing water pressure(e.g., by installing a water softener) to prevent future plumbing leaks.As another example, based upon, for example, an air flow analysis,dwelling analyzer 2212 may have detected that damaged frames and/ordividers allow air leaks into dwelling 2200. Thus, dwelling analyzer2212 may make recommendations with regards to window replacement/repairneeds. At 2360, dwelling analyzer 2212 preferably analyzes currentpolicy of a policy holder residing at dwelling 2200 with respect toeither immediate and/or preventive needs identified at steps 2356 and2358. For example, dwelling analyzer 2212 may determine whether policyholder's current policy covers any of the identified maintenance/repairneeds. In response to determining that the current policy does not coveridentified immediate/preventive repair and/or maintenance issues (step2362, no branch), dwelling analyzer 2212, at 2366, preferably recommendsone or more current policy modifications based on the analysis performedat step 2360. For example, if dwelling analyzer 2212 determines that thecurrent policy of the dwelling resident does not cover any of thepreventive repairs, a recommendation may be made to add such coverage tothe pre-existing policy.

In response to determining that current policy covers some or all of theidentified immediate/preventive repair and/or maintenance needs (step2362, yes branch), dwelling analyzer 2212, at 2364, preferablydetermines potential claim amount. For example, dwelling analyzer 2212may determine the total amount of benefits potentially payable on claimsassociated with identified needs, if the policyholder chooses to makeone or more claims against the insurance policy. In this step, dwellinganalyzer 2212 may derive the total amount of benefits based upon, forexample, the total repair estimate amount. The total repair estimateamount may include both a labor estimate and a parts estimate.

At 2368, dwelling analyzer 2212 preferably selects one or more preferredmaintenance/repair vendors. Maintenance/repair vendors are separateentities, each with the capability to perform a particular type ofrepair. For example, one vendor may specialize in insurance restorationwork on roofing, siding, gutters and windows. Another vendor may havethe capability to repair and fix the gas leak. Thus, dwelling analyzer2212 may select one or more preferred vendors based, at least in part,on data collected from sensors 2004. In an embodiment of the presentdisclosure, the preferred vendors can have exclusive capabilities,meaning that the capability to handle any one particular repair by onevendor is not shared by the remaining vendors. In an alternativeembodiment, the preferred vendors can have nonexclusive capabilities,meaning that the capability to handle any one repair service by any onevendor is shared by one or more remaining vendors. Moreover, thecapabilities of various vendors to handle the same type of repair mayinvolve different technologies and charges (i.e., costs). The preferredvendor list may be stored, for example, in insurance server 2012database.

At 2370, dwelling analyzer 2212 preferably provides a notification of apotential claim against the policyholder's insurance policy. It is to beappreciated that dwelling analyzer 2212 may be configured to deliver allnotifications regarding the potential claim corresponding to thedetermined repair/maintenance services electronically. The notificationcan be anything that advises a policy holder, device, or computer systemof the maintenance/repair issue, including but not limited to, a displayof text on a local display screen, a message in an email sent to a localor remote computer, a text message, a communication to a remote computersystem. The electronic delivery may include integration of notificationfunctionalities. It is to be also understood and appreciated thatdwelling analyzer 2212 may be configured and operational to integratewith policy holder's communicative computing devices (e.g., smart phones(via an app), computers, tablets, smart TV's, vehicle communicationsystems, etc.) for sending such notifications regarding such potentialinsurance claims. In an embodiment of the present disclosure, eachnotification may include, but not limited to, one or more immediaterepair and/or preventive repair (maintenance) needs, the total amount ofbenefits potentially payable on corresponding claim(s), preferredrepair/maintenance vendors and any additional information related to thepotential insurance claim.

Additionally, recommendations may be made with regards to appliances2230-2238 in the dwelling 2200. FIG. 17 is a flow diagram of a process2390 of operational steps of the appliance analyzer module of FIG. 13 inaccordance with an illustrated embodiment. With reference to FIG. 17 ,at 2392, appliance analyzer 2214 preferably collects data from aplurality of appliance sensors 2240 (shown in FIG. 13 ). As already hasbeen discussed with respect to dwelling analyzer 2212, in the context ofFIG. 16 , contact between the dwelling computing device 2006 andappliance analyzer 2214 may be initiated by either the applianceanalyzer 2214 or dwelling computing device 2006. Following the initialcontact, appliance analyzer 2214 may receive data from the dwellingcomputing device 2006. It is to be understood data packets collectedfrom appliance sensors 2240 can be aggregated in dwelling computingdevice 2006 and sent as an aggregated packet to appliance analyzer 2214for subsequent analysis.

At 2394, appliance analyzer 2214 preferably processes the received data.For example, just like the dwelling analyzer 2212 discussed above,appliance analyzer 2214 may include a parser configured to parse theaggregated packet and classify the received data based on, for example,type of appliance corresponding to a particular subset of the receiveddata. Appliance analyzer 2214 may create a data structure for eachclassification. This step may further involve identifying a policyholder associated with dwelling 2200 in which the analyzed appliancesare located.

At 2396, appliance analyzer 2214 preferably determines the age of theappliances 2230-2238 or parts thereof and/or length of service of theappliances 2230-2238 based on data captured from sensors 2240. At 2398,appliance analyzer 2214 preferably analyzes operating parameters withrespect to appliances 2230-2238. This step may further involve analyzingenvironmental conditions in which appliances 2230-2238 operate. Forexample, appliance analyzer 2214 may use environmental data measuredwith a plurality of sensors 2004 situated at or near the analyzedappliances 2230-2238. The environmental data may be indicative oftemperature, humidity, pressure, averages of the foregoing measurementsover a time period, etc. More specifically, appliance analyzer 2214 maybe configured to identify maintenance/repair issues based uponenvironmental conditions in conjunction with operating parameters.

At 2400, appliance analyzer 2214 preferably identifies one or moremaintenance/repair issues with respect to appliances 2230-2238. Asnon-limiting examples, the maintenance/repair issue can be any one ormore of the following: a need for replacement of the appliance 2230-2238or a component thereof, a need for repair of the appliance 2230-2238 ora component thereof, a need for battery recharging, lifespan expired,lifespan below a predefined threshold, power inadequacy, applianceinoperability for intended purpose, inoperability of one or morefunctions (electrical and/or mechanical), network connectivity failure,and the like. For instance, appliance analyzer 2214 may detectperformance degradation of an appliance (e.g., refrigerator 2230) uponeither it's past operating performance efficiency and/or its operatingperformance falling outside of threshold values prescribed for it by amanufacturer. As another non-limiting example, appliance analyzer 2214may detect a dirty filter in another appliance (e.g., HVAC component2232) and/or may detect degradation in HV AC component 2232 performancelikely contributable to a dirty filter element.

At 2402, appliance analyzer 2214 preferably analyzes current applianceinsurance policy of a policy holder residing at dwelling 2200 withrespect to maintenance/repair issues identified at step 2400. Forexample, appliance analyzer 2214 may determine whether current policy ofthe policy holder covers any of the identified maintenance/repair needs.In response to determining that the current policy does not cover atleast one of the identified appliance maintenance/repair issues (step2404, no branch), appliance analyzer 2214, at 2406, preferablyrecommends one or more insurance policy modifications based on theanalysis performed at step 2360. For example, if appliance analyzer 2214determines that the current appliance insurance policy does not coverperformance degradation for any of the appliances 2230-2238 situatedwithin the dwelling 2200, a recommendation may be made to add suchcoverage to the pre-existing policy.

In response to determining that the current policy covers some or all ofthe identified appliance repair/maintenance issue (step 2404, yesbranch), appliance analyzer 2214, at 2408, preferably provides anotification of a potential claim against the policyholder's applianceinsurance policy. As previously noted, the notification can be anythingthat advises a policy holder, device, or computer system of theappliance maintenance/repair issue, including but not limited to, adisplay of text on a local display screen, a message in an email sent toa local or remote computer, a text message, a communication to a remotecomputer system. Appliance analyzer 2214, may further includeprogramming instructions to engage in a communication session over theInternet with a remote computer system associated with an appliancemanufacturer, an appliance vendor, a repair service entity, areplacement service entity, or an appliance information provider, andduring the communication session, obtain information related to service,replacement, maintenance, etc., in connection with one or more of theappliances 2230-2238. According an embodiment of the present disclosure,each notification provided at 2408 may list one or morerepair/maintenance needs, the total amount of benefits potentiallypayable if the policy holder chooses to initiate the potential insuranceclaims, preferred repair/maintenance vendors and any additionalinformation related to the potential insurance claim.

With certain illustrated embodiments described above, it is to beappreciated that various non-limiting embodiments described herein maybe used separately, combined or selectively combined for specificapplications. Further, some of the various features of the abovenon-limiting embodiments may be used without the corresponding use ofother described features.

The foregoing description should therefore be considered as merelyillustrative of the principles, teachings and exemplary embodiments ofthis disclosure, and not in limitation thereof.

With reference to the process 2430 of FIG. 18 , at 2432, dwellinganalyzer 2212 preferably collects data from sensors 2004 to determine anumber of people occupying the dwelling 2200 at various points in timefor insurance purposes. In an embodiment of the present disclosure, thisstep may involve computing device 2006 periodically contacting (vianetwork 1 00), at prescribed time intervals, data analyzer component2218 running on server 2012 to send data collected by a plurality ofmotion sensors 2004. It is noted, a variety of motion sensors 2004 arepreferably installed at various points around the dwelling 2200 such asin the living room, bedroom, kitchen, and bathroom. The sensors arearranged to communicate with the computing device 2006, which, forexample, may be located in a hallway near a main entrance of thedwelling 2200. The one or more motion sensors 2004 may be configured andoperational to monitor movement of dwelling inhabitants in differentareas of the dwelling 2200. In an embodiment of the present disclosure,motion sensors 2004 may comprise passive infra-red detectors. Dwellinganalyzer 2212 may determine, for example, whether the dwelling 2200 wasoccupied by more than one inhabitant by detecting substantiallysimultaneous motion patterns at various points around the dwelling 2200.

At 2434, dwelling analyzer 2212 preferably processes the informaticsdata collected by a plurality of motion sensors 2004 to determine dailyrest-activity pattern. For example, dwelling analyzer 2212 may estimaterest-activity parameters such as bed time, rise time, sleep latency, andnap time for one or more inhabitants of the dwelling 2200 by combiningdata from multiple sensors 2004 located around the dwelling 2200. Asanother example, dwelling analyzer 2212 may be configured to determinewhether the dwelling remains unoccupied for an extended period of time.This information may be used by policy analyzer 2216, for instance, todetermine proper insurance coverage levels for personal propertycontained within the dwelling 2200.

At 2436, based on data collected from sensors 2004 regarding a dwelling2200, dwelling analyzer 2212 preferably conducts an analysis todetermine daily cooking activity pattern of one or more dwelling 2200inhabitants. In an embodiment of the present disclosure, one or moreappliance sensors 2004 may be employed to measure the use of cookingappliances such as a kettle, a fridge, a washing machine, a microwaveoven or an electric cooker. For example, dwelling analyzer 2212 maydetect the cooking time trends by detecting that a rice cooker ormicrowave oven is turned on/off, detecting that a gas range or an IH(Induction-Heating) cooking heater is turned on/off or detecting othercooking home electric appliances are turned on/off. As another example,dwelling analyzer 2212 may combine data collected from various types ofsensors, such as motion and appliance sensors 2004, to determine, forinstance, whether any of the cooking appliances remain unattended for anextended period of time, thus increasing the risk of fire. The dailycooking activity tracking may be adaptive. In other words, dwellinganalyzer 2212 preferably gradually adjusts to the dwelling inhabitant'snew activities and/or habits if they change over time. In general,dwelling analyzer 2212 may assess the risk of fires and explosionsarising from various activities of dwelling inhabitants and/or observedevents and use this information to provide targeted specific advice andguidance at dwelling 2200 to reduce the chance of fires and explosionsarising from the activity.

At 2438, dwelling analyzer 2212 conducts an analysis to determine dailywater consumption pattern. For example, based upon analysis of aplumbing system, dwelling analyzer 2212 may have detected long-termstress on pipes and may estimate future plumbing leaks. In order toprevent water leaks, dwelling analyzer 2212 may recommend reducing waterpressure (e.g., by installing a water softener). As another example,dwelling analyzer 2212 may have detected that dwelling 2200 inhabitantstend to leave shower faucets running while answering the phone, thusincreasing the risk of flooding in a bathroom. Dwelling inhabitants'behavior patterns during a storm can also increase the risk of flooding.For example, a combination of washing clothes, taking a shower, andrunning the dishwasher could add water to a system that may already beoverloaded. The water may have nowhere to go but into the basement ofthe dwelling 2200. Thus, dwelling analyzer 2212 may flag certain waterconsumption patterns of dwelling inhabitants as hazardous and use thisinformation to provide targeted specific advice and guidance to reducethe water leaks at dwelling 2200.

Similarly, at 2440, dwelling analyzer 2212 preferably performs ananalysis to determine daily energy consumption pattern. For example,based upon analysis of the dwelling's 2200 electrical system, dwellinganalyzer 2212 may have detected the load pattern and energy amount aredifferent in weekdays and weekends. For instance, during the weekday theminimum load may occur between 2:00 and 6:00 in the morning when most ofdwelling occupants are sleeping and morning peak may be betweenapproximately 7:00 AM and 10:00 AM, while the night peak may occurbetween approximately 7:00 PM and midnight when the dwelling 2200inhabitants are at home, making dinner and using the entertainmentappliances. On weekends there might be a mid-day peak load betweenapproximately 10:00 AM and 03:00 PM, while night peak may occur betweenapproximately 07:00 PM and 10:00 PM. In addition, in this step, dwellinganalyzer 2212 may flag certain energy consumption patterns of dwellinginhabitants as hazardous.

Thus, in steps 2432-2440, dwelling analyzer 2212 collects variouscharacteristics indicative of habits and trends of dwelling 2200inhabitants. At 2442, dwelling analyzer 2212 preferably transmits thesecharacteristics to policy analyzer module 2214. In an embodiment of thepresent disclosure dwelling 2200 inhabitants' habits and trendscharacteristics may include, but not limited to, daily water consumptionand energy consumption patterns, daily cooking activity pattern, numberof inhabitants, hazardous activities pattern, and the like. In analternative embodiment, dwelling analyzer 2212 may store these habitsand trends characteristics in insurance server 2012 database. Thereadings of the amount of energy/water used at dwelling 2200 can be usedto analyze and forecast an expected energy/water bill. This can also beused for budgeting and finance management because a history ofenergy/water usage at the dwelling 2200 or certain appliances can bemeasured and displayed to the homeowner or insurance company. Thesereadings and usage can be provided to the homeowner so that he canbudget X amount of money each month for the energy/water bill. Also, thehomeowner or insurer can track energy/water use and determine based uponthe rate of energy consumption that the homeowner is on a pace to usemore or less energy/water use than is budgeted. If the homeowner is onpace to use more energy/water than is budgeted the insurance company canprovide advice and guidance on how the homeowner can reduce energy use.If the homeowner is on pace to use less energy/water than is budgetedthe insurance company can help the homeowner in moving the unspentportion of the budget amount to a savings device like a CD or moneymarket.

FIG. 19 is a flow diagram of a process 2460 of operational steps of thepolicy analyzer module of FIG. 13 in accordance with an illustratedembodiment. At 2462, policy analyzer 2216 preferably receives dwelling2200 habits and trends information from the dwelling analyzer 2212. Inan alternative embodiment of the present disclosure, this step mayinvolve the policy analyzer 2216 retrieving habits and trendsinformation from the insurance server's 2012-storage component. Next,policy analyzer 2216 preferably maps the received/retrieved data to aparticular insurance policy associated with the dwelling 2200.

At 2464, policy analyzer 2216 preferably analyzes the insurance policyassociated with the dwelling 2200. For example, policy analyzer 2216 mayidentify the type of the insurance policy. In other words, policyanalyzer 2216 may determine whether the corresponding policy compriseshomeowner's insurance, renter's insurance, umbrella liability insurance,and the like. In addition, policy analyzer 2216 preferably determineswhether the insurance policy covers damage to or destruction of thedwelling 2200, whether it covers damage to or destruction of detachedstructures and whether it covers a plurality of appliances in thedwelling 2200 amongst other coverages.

According to an embodiment of the present disclosure, at 2466, policyanalyzer 2216 checks whether the identified insurance policy type isrenter's insurance. Such insurance typically covers personal propertywithin a dwelling and policy holders typically do not own the structurethey occupy. This type of policy can also cover liabilities arising fromaccidents and intentional injuries for guests of a covered dwelling. Inresponse to determining that dwelling 2200 is covered by the renter'sinsurance policy (step 2466, yes branch), at 2468, policy analyzer 2216may determine additional coverage details associated with this type ofpolicy. For instance, policy analyzer 2216 may identify personalproperty within the dwelling 2200 that is covered by the insurancepolicy. Such property may include, but not limited to, jewelry,furniture, musical instruments, electrical and/or kitchen appliances,guns, furs, various items of fine art and antiques, collectible items,valuable papers, business property, and the like. This step may alsoinvolve policy analyzer 2216 determining property coverage limits aswell as estimating the cost to replace the policyholder's personalbelongings. While steps 2466 and 2468 are discussed with reference torenter's insurance policy, it is understood that this discussion isprovided for illustrative purposes only. A person skilled in therelevant art will recognize that policy analyzer

2214 may determine other types of information relevant to the specifictype of the insurance policy without departing from the scope and spiritof the presently disclosed embodiments.

In response to determining that dwelling 2200 is covered by other typeof insurance policy (step 2466, no branch), policy analyzer 2216, at2470, preferably determines change recommendations to insuranceproducts/services (that may be either currently existing ornon-existing) which may be beneficial to a policy holder in view ofcurrent subscribed insurance products and coverage levels (i.e., currentpolicy coverage levels). Policy analyzer 2216 preferably makes suchdetermination based on data collected by the dwelling analyzer 2212 andbased on analysis conducted at 2464. For instance, if policy analyzer2216 determined that a policy holder (i.e., homeowner or renter) may nothave insurance covering a particular type of event/loss, and based uponcollected and analyzed data from sensors 2004 (amongst possible otherfactors), dwelling analyzer 2214 may provide a recommendation to apolicyholder to subscribe to insurance covering such a particular typeof event/loss. Additionally, policy analyzer 2216 may provide arecommendation to increase, decrease, or make other adjustments topersonal liability limits based upon detected trends and habitsdetermined by the dwelling analyzer 2212 at least in part by datacollected from certain sensors 2004. In an embodiment of the presentdisclosure, such recommendation may relate to any damage associated withthe dwelling 2200. As another example, one or more suggestedmodifications may relate to a loss of one or more of the personalproperty items associated with the dwelling 2200.

At 2472, policy analyzer 2216 preferably provides a notificationindicating suggested insurance coverage modifications. It is to beappreciated that policy analyzer 2216 may be configured toelectronically deliver all notifications regarding suggested insuranceproducts modifications based on detected habits and trends of thedwelling 2200 inhabitants. The notification can be anything thatsecurely advises a policy holder, device, or computer system of thesuggested changes, including but not limited to, a display of text on alocal display screen, a message in an email sent to a local or remotecomputer, a text message, a communication to a remote computer system.It is to be also understood and appreciated that policy analyzer 2216may be configured and operational to integrate with policy holder'scommunicative computing devices (e.g., smart phones (via an app),computers, tablets, smart TV's, vehicle communication systems, etc.) forsending such notifications regarding such suggested insurancemodifications. In an embodiment of the present disclosure, eachnotification may include, but not limited to, detected habits and trendsas well as suggested recommendations with respect to insuranceproducts/services associated with the dwelling 2200.

With reference to the process 2490 of FIG. 20 , at 2492, dwellinganalyzer 2212 preferably collects data from sensors 2004. In anembodiment of the present disclosure, this step may involve computingdevice 2006 periodically contacting (via network 2000), at prescribedtime intervals, data analyzer component 2218 running on server 2012 tosend accumulated data. In an alternative embodiment, contact between thedwelling computing device 2006 and dwelling analyzer 2212 may beinitiated when the dwelling analyzer 2212 contacts the dwellingcomputing device 2006. Following the initial contact, dwelling analyzer2212 may receive data from the dwelling computing device 2006. It is tobe understood data packets collected from sensors 2004 can be aggregatedin dwelling computing device 2006 and send as an aggregated packet todwelling analyzer 2212 for subsequent analysis.

At 2494, dwelling analyzer 2212 preferably processes the informaticsdata collected by a plurality of sensors 2004 to assess environmentalconditions related to the dwelling 2200. Environmental conditions mayinclude, but are not limited to: temperature conditions, windconditions, air quality present in the dwelling 2200, humidity presentin the dwelling 2200, and so forth. In various embodiments of thepresent disclosure, the plurality of sensors 2004 measuring and/orcollecting environmental informatics data may include one or more oftemperature sensors, humidity sensors, sound sensors, wind speedsensors, environmental sensors, and so on. In an embodiment of thepresent disclosure, dwelling analyzer 2212 may collect data from morethan one dwelling in a geographic area to determine the general level ofrisk in the area. For example, dwelling analyzer 2212 may analyze thedata from approximately ten houses in a particular geographic locationto determine that average wind speed has been increasing over the pastfew years. As another example, dwelling analyzer 2212 may determinewhether a particular geographic area in which the dwelling 2200 islocated is prone to earthquakes based on recent seismic activitymeasured by various environmental sensors 2004. This information may beused by policy analyzer 2216, for instance, to determine properinsurance coverage alterations.

At 2496, based on data collected from sensors 2004 regarding dwelling2200, dwelling analyzer 2212 preferably conducts an analysis todetermine a structural condition of the dwelling 2200. For example,dwelling analyzer 2212 may determine whether harsh environmentalconditions, such as hurricane, storm surge, earthquake, volcano,landslide, and the like, have affected structural integrity of thedwelling 2200. In addition to the above, some geographic regionscommonly experience problems that cannot only be a nuisance to thoseliving in the residence, but which can also destroy the structuralintegrity of the dwelling structure itself. For example, termites arejust one type of insect that are known to infest and damage homes. Thus,dwelling analyzer 2212 may conduct an analysis to detect dangerousinsect infestations within the dwelling 2200 structure. As yet anothernon-limiting example, in this step dwelling analyzer 2212 may detect ahole in the roof of the dwelling 2200 requiring immediate repair. Ingeneral, at 2496, dwelling analyzer 2212 may analyze the collected datato determine whether dwelling 2200 and/or any of its components satisfystructural soundness requirements.

At 2498, dwelling analyzer 2212 conducts an analysis to determine amaintenance score value corresponding to the dwelling 2200. For example,dwelling analyzer 2212 may generate the maintenance score value basedupon the dwelling age, dwelling type and any repair and/or maintenanceneeds identified at 2494 and 2496. It is noted that repair/maintenanceneeds may include, but not limited to, immediate repair needs andpreventive maintenance needs. In general, any dwelling condition thataffects the residents' health or safety may be considered by dwellinganalyzer 2212 as requiring an immediate repair. For instance a hole mayhave been detected in the roof of dwelling 2200 (via one or more sensors2004), requiring immediate repair. As another example, an environmentalsensor may have detected a gas leak or any contaminant adverse to humanhealth. As an example of preventive maintenance needs, based upon an airflow analysis, dwelling analyzer 2212 may have detected that damagedframes and/or dividers allow air leaks into dwelling 2200. Thus,dwelling analyzer 2212 may consider window replacement as a preventivemaintenance factor in calculation of the maintenance score value. Thegenerated maintenance score may be represented in the form of anumerical value, such as a value ranging from 0 to 5 for each of thefactors, as well as a combined (average or weighted average) aggregatescore.

In other illustrative embodiments, dwelling analyzer 2212 is configuredand operational to update the insurance policy if an alteration to thedwelling 2200 has been detected (e.g., structural and/or appliancerelated). Additionally, dwelling analyzer 2212 is configured andoperational to trigger an inspection requirement upon the aforesaiddetection of an alteration to the dwelling 2200.

As previously noted, dwelling 2200 may contain a plurality of applianceslocated therein or in its vicinity. Accordingly, at 2500, dwellinganalyzer 2212 preferably performs an analysis of data collected fromsuch appliances, such as their age, operating parameters,maintenance/repair issues, and the like. This step may further involveanalyzing environmental conditions in which appliances operate. Forexample, dwelling analyzer 2212 may use environmental data measured witha plurality of sensors 2004 situated at or near the analyzed appliances.The environmental data may be indicative of temperature, humidity,pressure, averages of the foregoing measurements over a time period,etc. More specifically, dwelling analyzer 2212 may be configured toidentify maintenance/repair issues based upon environmental conditionsin conjunction with operating parameters. In addition, dwelling analyzer2212 may detect performance degradation of an appliance (e.g.,refrigerator) upon either it's past operating performance efficiencyand/or its operating performance falling outside of threshold valuesprescribed for it by a manufacturer. As another non-limiting example,dwelling analyzer 2212 may detect a dirty filter in another appliance(e.g., HVAC component) and/or may detect degradation in HV AC componentperformance likely contributable to a dirty filter element.

Next, at 2252, dwelling analyzer 2212 preferably determines habits andtrends of dwelling 2200 inhabitants based on collected informaticssensor data. In an embodiment of the present disclosure, one or moreappliance sensors I 02 may be employed to measure the use of cookingappliances such as a kettle, a fridge, a washing machine, a microwaveoven or an electric cooker. For example, dwelling analyzer 2212 maydetect the cooking time trends by detecting that a rice cooker ormicrowave oven is turned on/off, detecting that a gas range or an IH(Induction-Heating) cooking heater is turned on/off or detecting othercooking home electric appliances are turned on/off. As another example,dwelling analyzer 2212 may combine data collected from various types ofsensors, such as motion and appliance sensors 2004, to determine, forinstance, whether any of the cooking appliances remain unattended for anextended period of time, thus increasing the risk of fire. The dailycooking activity tracking may be adaptive. In other words, dwellinganalyzer 2212 preferably gradually adjusts to the dwelling inhabitant'snew activities and/or habits if they change over time. As anothernon-limiting example, dwelling analyzer 2212 may flag certain determinedwater consumption and/or energy consumption patterns of dwellinginhabitants as hazardous. In general, dwelling analyzer 2212 may assessthe risk of fires, flooding, explosions and theft of personal property,amongst other risks, arising from various activities of dwellinginhabitants and/or events observed at the dwelling 2200.

Thus, in steps 2492-2252, dwelling analyzer 2212 analyzes variousconditions that are present at the dwelling 2200, in advance of anyactual damage event. At 22524, dwelling analyzer 2212 preferablytransmits this comprehensive dwelling 2200 assessment to policy analyzermodule 2214. In an embodiment of the present disclosure, thecomprehensive assessment data may include, but not limited to,dwelling's structural condition, maintenance score value, risky habitsand trends of dwelling inhabitants, environmental conditions related tothe dwelling 2200, and the like. In an alternative embodiment, dwellinganalyzer 2212 may store this information in insurance server 1 06database.

FIG. 21 is a flow diagram of a process 2520 of operational steps of thepolicy analyzer module of FIG. 13 in accordance with an illustratedembodiment. At 2522, policy analyzer 2216 preferably receives dwelling2200 assessment information from the dwelling analyzer 2212. In analternative embodiment of the present disclosure, this step may involvethe policy analyzer 2216 retrieving such information from the insuranceserver's 2012 storage component. Next, policy analyzer 2216 preferablymaps the received/retrieved data to a particular insurance policyassociated with the dwelling 2200.

At 2524, policy analyzer 2216 preferably analyzes the insurance policyassociated with the dwelling 2200 to further assess perceived dwellingexposure. For example, policy analyzer 2216 may identify the type of theinsurance policy and may identify one or more perils covered by thepolicy. As used herein, the term “peril” refers to a cause of loss. Byway of example, such perils (or perilous events) may include a naturaldisaster (e.g., a tornado, a hurricane, an earthquake, a flood, etc.), amanmade disaster (e.g. a release of hazardous material, gas pipeexplosion, arson, etc.), and the like. Coverage can be provided on an“all perils” basis, or a “named perils” basis. Named perils policiestypically list exactly what is covered by the policy, while open perils(or all perils) policies may list what is excluded from coverage. In anembodiment of the present disclosure, once policy analyzer 2216identifies all perils covered by the insurance policy, it preferablyevaluates levels of exposure for each peril based on observed and/orhistorical data provided by the dwelling analyzer 2212. As anillustrative example, policy analyzer 2216 may determine estimatedlikelihood that a specified peril (e.g., a tornado) may occur in aspecified geographical zone to cause a specified degree of damage (e.g.,10 million), based on environmental conditions analyzed by the dwellinganalyzer 2212. In an embodiment of the present disclosure, policyanalyzer 2216 may perform evaluation of the probable maximum loss(“PML”) corresponding to the dwelling 2200. Determining the PML for aproperty is conventionally treated as an evaluation of the costs likelyto be incurred in response to a particular loss event. For example, thisvaluation is typically determined simply as the replacement cost ofrestoring a dwelling in the event of a flood or rebuilding a structurefollowing a fire. It is noted that other types of decisions related tovarious policy alterations may be made by the dwelling analyzer 2212 at2524.

According to an embodiment of the present disclosure, at 2526, policyanalyzer 2216 checks whether the dwelling 2200 is eligible for a policydiscount. For example, discount on the insurance policy for the dwelling2200 may be provided based on the decision of an owner/operator of thedwelling to share data from sensors 2004 with an insurance carrier(e.g., insurance carrier server 2012). Maintaining (or providingadjustments to) the policy discount may be contingent upon the adherenceof certain conditions, such as maintenance of the dwelling structure, asdetermined by the dwelling analyzer 2212 based on data captured from thedwelling sensors 2004. In an embodiment of the present disclosure,policy analyzer 2216 may utilize the maintenance score to determine ifit satisfies a threshold score value prescribed by the insurance carrierto maintain policy discounts contingent upon prescribed maintenanceobligations.

In response to determining that the dwelling 2200 is eligible for apolicy discount (step 2526, yes branch), policy analyzer 2216, at 2528,may determine a policy discount value. Various factors that may beconsidered by the policy analyzer 2216 for determining the discountvalue may include, the age of the dwelling 2200, maintenance scorevalue, maintenance of protective devices (smoke alarms, deadbolts, fireextinguishers, fire alarms, burglar alarms, sprinklers, etc.). Aspreviously indicated, in an embodiment of the present disclosure,dwelling owner's adherence to an agreement of sharing data from sensors2004 with an insurance carrier may be an important determinant of thepolicy discount value. If policy analyzer 2216 determines that thedwelling 2200 is not eligible for the policy discount (step 2526, nobranch), it may proceed with determining other potential alterationsrelated to the insurance policy. For example, at 2530, policy analyzer2216 may determine adjustments to coverage limits based on the dataprovided by the dwelling analyzer 2212. Insurance policies are typicallyreplacement-driven. Accordingly, policy analyzer 2216 may determineinsurance policy coverage limits for dwelling 2200 based on theestimated cost to replace the dwelling 2200 covered by the policy in theevent of a loss. In various embodiments of the present disclosure,policy analyzer 2216, may consider dwelling assessment attributesprovided by the dwelling analyzer 2212, such as the age of the dwelling,maintenance score value, risky habits and trends of dwellinginhabitants, environmental conditions related to the dwelling, thepresence of sprinkler systems, and the like, to reduce or increasecoverage limits.

Next, at 2532, policy analyzer 2216 optionally determines potentialadjustments to insurance policy premiums. Just like coverage limits,insurance policy premium adjustments may be based on the estimatedreplacement cost of the dwelling 2200 and/or estimated replacement costof personal property located therein. If policy analyzer 2216 determined(at 2526) that the dwelling is eligible for policy discount, in thisstep, policy analyzer 2216 may reduce premium value based on thedetermined discount value. Advantageously, the analysis performed by thepolicy analyzer 2216 may account for dwelling inhabitants' habits andtrends. For example, fires are most often caused by owners' andresidents' bad habits, common mistakes, or negligence. Therefore, ifdwelling analyzer 2212 determines that the cooking appliances remainunattended in the dwelling 2200 for an extended period of timefrequently, thus increasing the risk of fire, policy analyzer 2216 mayincrease policy premiums accordingly. Conversely, if dwelling analyzer2212 determines that dwelling inhabitants have no habits that mayincrease the risk of peril, policy analyzer 2216 may decrease policypremiums as a result.

If at 2524 policy analyzer 2216 determined that the insurance policyassociated with the dwelling 2200 includes liability coverage, at 2534,policy analyzer 2216 may make adjustments to such liability coveragebased on data provided by the dwelling analyzer 2212. Liability sectionof the insurance policy typically provides coverage in the event adwelling inhabitant/operator is legally responsible for injury toothers. The analysis performed by the policy analyzer 2216 in this stepmay also account for dwelling inhabitants' habits and trends, asdescribed above.

At 2536, policy analyzer 2216 preferably provides a notificationindicating suggested insurance policy alterations. It is to beappreciated that policy analyzer 2216 may be configured toelectronically deliver all notifications regarding suggested insurancepolicy modifications. The notification can be anything that advises apolicy holder, device, or computer system of the suggested changes,including but not limited to, a display of text on a local displayscreen, a message in an email sent to a local or remote computer, a textmessage, a communication to a remote computer system. The electronicdelivery may include integration of notification functionalities intosocial networking services (e.g., via Facebook, Twitter, and the like).It is to be also understood and appreciated that policy analyzer 2216may be configured and operational to integrate with policy holder'scommunicative computing devices (e.g., smart phones (via an app),computers, tablets, smart TV's, vehicle communication systems, kitchencommunication systems, etc.) for sending such notifications regardingsuch suggested insurance policy alterations. In an embodiment of thepresent disclosure, each notification may include, but not limited to,adjusted coverage limits and premiums, liability coverage adjustments,and the like.

FIG. 22 is a flow diagram of operational steps 2550 of the policyanalyzer module of FIG. 13 in accordance with an illustrated embodiment.At 2552, policy analyzer 2216 preferably receives dwelling 2200assessment information from the dwelling analyzer 2212. In analternative embodiment of the present disclosure, this step may involvethe policy analyzer 2216 retrieving such information from the insuranceserver's 2012 storage component. Next, policy analyzer 2216 preferablymaps the received/retrieved data to a particular insurance policyassociated with the dwelling 2200.

At 2554, policy analyzer 2216 preferably analyzes the insurance policyassociated with the dwelling 2200 to further assess perceived dwellingexposure. For example, policy analyzer 2216 may identify the type of theinsurance policy and may identify one or more perils covered by thepolicy. As used herein, the term “peril” refers to a cause of loss. Byway of example, such perils (or perilous events) may include a naturaldisaster (e.g., a tornado, a hurricane, an earthquake, a flood, etc.), amanmade disaster (e.g. a release of hazardous material, gas pipeexplosion, arson, etc.), and the like. Coverage can be provided on an“all perils” basis, or a “named perils” basis. Named perils policiestypically list exactly what is covered by the policy, while open perils(or all perils) policies may list what is excluded from coverage. Thus,in an embodiment of the present disclosure, policy analyzer 2216 mayidentify perils and/or other risks excluded from coverage.

At 2556, policy analyzer 2216 preferably identifies one or more policyalterations based on the analysis conducted at 2554 and based ondwelling assessment information received from the dwelling analyzer2212. Such policy alterations may include, but are not limited to,policy discount modifications, adjustments to coverage limits, premiumadjustments, and the like. For example, discount on the insurance policyfor the dwelling 2200 may be provided based on the decision of anowner/operator of the dwelling to share data from sensors 2004 with aninsurance carrier (e.g., insurance carrier server 2012). Maintaining (orproviding adjustments to) the policy discount may be contingent upon theadherence of certain conditions, such as maintenance of the dwellingstructure, as determined by the dwelling analyzer 2212 based on datacaptured from the dwelling sensors 2004. Advantageously, the analysisperformed by the policy analyzer 2216 may account for dwellinginhabitants' habits and trends. For example, fires are most often causedby owners' and residents' bad habits, common mistakes, or negligence.Therefore, if dwelling analyzer 2212 determines that the cookingappliances remain unattended in the dwelling 2200 for an extended periodof time frequently, thus increasing the risk of fire, policy analyzer2216 may increase policy premiums accordingly.

At 2558, policy analyzer 2216 preferably determines a coverage gapassociated with a natural disaster, such as, for example, but notlimited to, an earthquake, hurricane, tornado, typhoon, flood, fire, andthe like. In an embodiment of the present disclosure, once policyanalyzer 2216 identifies all perils covered by the insurance policy, itpreferably evaluates levels of exposure for each peril based on observedand/or historical data provided by the dwelling analyzer 2212. As anillustrative example, policy analyzer 2216 may determine estimatedlikelihood that a specified peril (e.g., a tornado) may occur in ageographical zone corresponding to dwelling's 2200 location, based onenvironmental conditions (i.e., wind speed measurements) analyzed by thedwelling analyzer 2212. In an embodiment of the present disclosure,policy analyzer 2216 may perform evaluation of the probable maximum loss(“PML”) corresponding to the dwelling 2200. Determining the PML for aproperty is conventionally treated as an evaluation of the costs likelyto be incurred in response to a particular loss event. In addition,policy analyzer 2216 may determine whether any additional coverage (notcovered by the current policy) may be provided. For example, homeowner'spolicies generally exclude most or all damage to the property from flood(including hurricane storm surge), earth movement (due to settling,shrinking, expansion, earthquake, volcano and landslide), pollution,war, and nuclear accidents. As another example, if policy analyzer 2216determines that estimated likelihood of earthquake occurrence issufficiently high, in response, policy analyzer 2216 may recommendearthquake coverage, for example, as a separate insurance policy. It isnoted that policy analyzer 2216 may provide similar recommendations withrespect to other natural disasters based on the analysis performed bythe dwelling analyzer 2212. In various embodiments of the presentdisclosure, policy analyzer 2216, may consider dwelling assessmentattributes provided by the dwelling analyzer

2212, such as the age of the dwelling, maintenance score value, riskyhabits and trends of dwelling inhabitants, environmental conditionsrelated to the dwelling, the presence of sprinkler systems, and thelike, to reduce or increase coverage limits.

At 2560, policy analyzer 2216 preferably determines a coverage gapassociated with general liability insurance. Liability section of theinsurance policy typically provides coverage in the event a dwellinginhabitant/operator is legally responsible for injury to others. It isnoted that homeowner's policies typically have a variety of liabilityexclusions. For example, the homeowner's policy may exclude coverage forinjuries to any tenants when more than two of them reside in the covereddwelling. So, if dwelling analyzer 2212 determines that three upstairsbedrooms in the dwelling 2200 are rented, policy analyzer 2216 mayrecommend, for instance, a commercial policy for rooming houses. Asanother non-limiting example, if dwelling analyzer 2212 determines thata pet (i.e., a dog) resides with one of the tenants in the dwelling2200, the current insurance policy may not cover the landlord of thedwelling 2200 for tenant's dog biting someone on the dwelling premises.As a result, the landlord may be held responsible for the injuries.Thus, policy analyzer 2216 may recommend to increase general liabilitycoverage to provide additional protection for the policy holder (i.e.,landlord).

Next, at 2562, policy analyzer 2216 optionally determines a coverage gapassociated with personal property. Personal property coverage typicallypays for a loss of policy holder's personal possessions, such asclothing, furniture, TV, stereo and other unattached personal items. Inan embodiment of the present disclosure, policy analyzer 2216 mayevaluate current policy to determine if additional coverage for highervalued items may be needed. For instance, a homeowner's insurance policynormally provides limited coverage for collectibles, jewelry, furs, andthe like. Thus, policy analyzer 2216 may recommend an additionalinsurance product, such as, for example, a personal property floater. Apersonal property floater may itemize each item, describe the iteminsured, and list excluded perils. A personal property floater normallyprovides coverage that is broader than the coverage in standardhomeowners insurance policy. Thus, in this step, policy analyzer 2216may evaluate policy holder's risk in this area, based on the dwellingassessment attributes provided by dwelling analyzer 2212, and mayrecommend a diversity of insurance products that may address such risk.

As previously noted, dwelling 2200 may contain a plurality of applianceslocated therein or in its vicinity. Some of the risks involvingappliances may be covered under a homeowner's policy associated with thedwelling 2200, while other risks may not be covered. For instance,normal wear and tear to appliances typically is not covered under ahomeowner's insurance policy. At 2564, policy analyzer 2216 may analyzemaintenance/repair issues identified by dwelling analyzer 2212, in orderto recommend an insurance product that may provide adequate protectionfor the homeowner. For example, policy analyzer 2216 may recommend anappliance breakdown coverage or home warranty insurance plans. Theseplans typically cover the gap left by homeowner's insurance. A list ofappliances that may be covered by the appliance breakdown coverage planincludes, but is not limited to, washers and dryers, computers,dishwashers, refrigerators and freezers, ovens and microwaves, garbagedisposals, heat pumps, heating and air conditioning systems, electricalservice panels, home security systems, water heaters, well water pumps,sump pumps, surround sound systems, swimming pool equipment,televisions, and the like. As a non-limiting example, if dwellinganalyzer 2212 detects a surge in electric power that may damage one ormore appliances in the dwelling 2200, in response, policy analyzer 2216may recommend an insurance product that would provide breakdown coveragefor such appliances.

At 2566, policy analyzer 2216 preferably determines replacement cost forthe dwelling 2200 and/or personal property located therein. In anembodiment of the present disclosure, this step may involve policyanalyzer 2216 determining the PML in relation to a particular lossevent. For example, this valuation may be determined as the replacementcost of restoring the dwelling 2200 in the event of a flood orrebuilding a structure following a fire. Accordingly, policy analyzer2216 may recommend an adjustment to the current policy. For example,replacement cost estimates may be influenced by supply of labor, demandfor labor, and the cost of construction materials. Thus, policy analyzer2216 may recommend to change the coverage amount to maintain coverage atleast equal to 100 percent of the estimated replacement cost coveragefor the dwelling 2200.

At 2568, policy analyzer 2216 optionally determines a need for anumbrella insurance policy. Umbrella insurance refers to an insurancepolicy that protects the assets and future income of the policyholderabove and beyond the standard limits set on their primary (i.e.,underlying) insurance policies. Typically, an umbrella policy is pureliability coverage over and above the coverage afforded by theunderlying policy. The term “umbrella” is used because it coversliability claims from all policies underneath it. For example, if apolicyholder has a homeowner's policy with a limit of $300,000 and anearthquake policy with a limit of $500,000, then with a million dollarumbrella insurance policy, policyholder's combined limits become ineffect, i.e. $1,300,000 on a homeowner's liability claim and $1,500,000on an earthquake claim.

Umbrella insurance may also provide coverage for claims that may beexcluded by the primary policies. Thus, instead of recommending toincrease general liability coverage, as discussed above in connectionwith step 2560, at 2568 policy analyzer 2216 may recommend an umbrellainsurance policy. If at 2554 policy analyzer determines that thedwelling 2200 is already covered by an umbrella insurance policy, at2568 policy analyzer 2216 may automatically determine whether anadjustment is needed to the dwelling's current umbrella policy, forexample, in view of the suggested changes to the underlying homeowner'sinsurance policy. For instance, if the policy analyzer 2216 recommends(e.g., at 2564) to add one or more appliances to the underlyinginsurance policy or policies, then additional umbrella coverage may beneeded based on that additional appliance added to the policy. Inaddition, policy analyzer 2216 may determine that an adjustment isneeded to the current umbrella policy in view of the hazardous habits ofdwelling occupants, which may have been detected by the dwellinganalyzer 2212. At 2570, policy analyzer 2216 preferably automaticallygenerates a comprehensive set of insurance products recommendationsbased on the analysis performed at steps 2554-2568. In an embodiment ofthe present disclosure, policy analyzer 2216 may be configured togenerate a predetermined number of insurance product recommendationsbased, for example, on correlation degrees of various insurance productsassociated with the dwelling 2200. In addition, policy analyzer 2216 maydetermine a multiple policy discount value, which can apply tocombinations of multiple insurance policies.

At 2572, policy analyzer 2216 preferably provides a notificationindicating suggested insurance product recommendations. It is to beappreciated that policy analyzer 2216 may be configured toelectronically deliver all notifications regarding recommended insuranceproducts or services. The notification can be anything that advises apolicy holder, device, or computer system of the suggested changes,including but not limited to, a display of text on a local displayscreen, a message in an email sent to a local or remote computer, a textmessage, a communication to a remote computer system. The electronicdelivery may include integration of notification functionalities intosocial networking services (e.g., via Facebook, Twitter, and the like).It is to be also understood and appreciated that policy analyzer 2216may be configured and operational to integrate with policy holder'scommunicative computing devices (e.g., smart phones (via an app),computers, tablets, smart TV's, vehicle communication systems, kitchencommunication systems, etc.) for sending such notifications regardinginsurance product recommendations. In an embodiment of the presentdisclosure, each notification may include, but not limited to, adjustedcoverage limits and premiums, coverage adjustments, additional insuranceproducts and services, and the like. Additionally, policy analyzer 2216may save the aforementioned recommendations in the insurance server's2012 storage component. These recommendations may then be automaticallycommunicated to the policy holder and/or reflected in the policyholder's next insurance billing statement.

FIG. 23 shows, in the form of a flow chart, exemplary operational steps2590 of the appliance analyzer 2214. Before turning to description ofFIG. 23 , it is noted that the flow diagram shown therein is described,by way of example, with reference to components shown in FIGS. 11-13 ,although these operational steps may be carried out in any system andare not limited to the scenario shown in the aforementioned figures.Additionally, the flow diagram in FIG. 23 shows an example in whichoperational steps are carried out in a particular order, as indicated bythe lines connecting the blocks, but the various steps shown in thisdiagram can be performed in any order, or in any combination orsub-combination.

At 2592, appliance analyzer 2214 preferably collects data from aplurality of appliance sensors 2240 (shown in FIG. 13 ). Contact betweenthe dwelling computing device 2006 and appliance analyzer 2214 may beinitiated by either the appliance analyzer 2214 or dwelling computingdevice 2006. Following the initial contact, appliance analyzer 2214 mayreceive data from the dwelling computing device 2006. It is to beunderstood data packets collected from appliance sensors 2240 can beaggregated in dwelling computing device 2006 and sent as an aggregatedpacket to appliance analyzer 2214 for subsequent analysis.

At 2594, appliance analyzer 2214 preferably processes the received data.For example, appliance analyzer 2214 may include a parser configured toparse the aggregated packet and classify the received data based on, forexample, type of appliance corresponding to a particular subset of thereceived data. Appliance analyzer 2214 may create a data structure foreach classification. This step may further involve identifying a policyholder associated with dwelling 2200 in which the analyzed appliancesare located.

At 2596, appliance analyzer 2214 preferably determines the age of theappliances 2230-2238 or parts thereof and/or length of service of theappliances 2230-2238 based on data captured from sensors 2240. At 2598,appliance analyzer 2214 preferably analyzes operating parameters withrespect to appliances 2230-2238. This step may further involve analyzingenvironmental conditions in which appliances 2230-2238 operate. Forexample, appliance analyzer 2214 may use environmental data measuredwith a plurality of sensors situated at or near the analyzed appliances2230-2238. The environmental data may be indicative of temperature,humidity, pressure, averages of the foregoing measurements over a timeperiod, etc. More specifically, appliance analyzer 2214 may beconfigured to identify maintenance/repair issues based uponenvironmental conditions in conjunction with operating parameters.

At 2600, appliance analyzer 2214 preferably identifies one or moremaintenance/repair issues with respect to appliances 2230-2238. Asnon-limiting examples, the maintenance/repair issue can be any one ormore of the following: a need for replacement of the appliance 2230-2238or a component thereof, a need for repair of the appliance 2230-2238 ora component thereof, a need for battery recharging, lifespan expired,lifespan below a predefined threshold, power inadequacy, applianceinoperability for intended purpose, inoperability of one or morefunctions (electrical and/or mechanical), network connectivity failure,and the like. For instance, appliance analyzer 2214 may detectperformance degradation of an appliance (e.g., refrigerator 2230) uponeither it's past operating performance efficiency and/or its operatingperformance falling outside of threshold values prescribed for it by amanufacturer. As another non-limiting example, appliance analyzer 2214may detect a dirty filter in another appliance (e.g., HVAC component2232) and/or may detect degradation in HVAC component 2232 performancelikely contributable to a dirty filter element.

At 2602, appliance analyzer 2214 preferably determines whetheraccidental damage protection is needed with respect to appliances2230-2238. For example, if appliance analyzer 2214 determines that oneor more of the appliances 2230-2238 is in need of replacement or repairdue to accidental damage, appliance analyzer 2214 may recommend acorresponding accidental damage protection insurance product. In aparticular embodiment of the disclosure, the accidental damage coveragemay cover accidental damage to the appliance 2230-2238 (such as damagecaused by accidentally dropping appliance 2230-2238), and/or other lossof the appliance 2230-2238 (e.g., loss of the appliance 2230-2238through theft, fire, storm, burglary, natural disasters, or otherperil). As another example, accidental damage protection may coveraccidental discharge, leakage or overflow of water or steam from withina plumbing, heating or HVAC system 2232, sudden and accidental tearingapart, cracking, burning or bulging of a steam or hot water heatingsystem or of appliances for heating water, sudden and accidental damagefrom artificially generated currents to electrical appliances, devices,fixtures and wiring. Accordingly, if analysis of the applianceinformatics data detects, for example, leakage or overflow of water,appliance analyzer 2214 may recommend accidental damage protection forone or more of the appliances 2230-2238 that may be damaged by suchleakage or overflow.

At 2604, appliance analyzer 2214 preferably determines whether extendedwarranty coverage is needed with respect to appliances 2230-2238. In anembodiment of the present disclosure, an extended warranty may be aninsurance product that can be purchased to cover the repair costs ofproduct support or repair services beyond the warranty provider'soriginal warranty period. An extended warranty may allow thepolicyholder to receive support and product repair services above andbeyond what is provided by a base warranty associated with appliances2230-2238. An extended warranty may take the form of a flexible durationextended warranty or a fixed duration extended warranty.

When offering flexible or fixed duration extended warranty coverage,appliance analyzer 2214 may seek to charge a premium that both enticespolicyholders and results in profit. For example, the appliance analyzer2214 may offer a flexible extended warranty with a premium that isattractive to the policyholder because it can reduce expected supportcosts over the life of one or more appliances 2230-2238 covered by thewarranty. In an embodiment of the present disclosure, appliance analyzer2214 may place restrictions on an extended warranty product. Forexample, a flexible duration extended warranty can come with arestriction such that if a policyholder purchases coverage, the coverageshould be started before the product reaches a pre-specified age. Aflexible duration extended warranty can also come with a restrictionsuch that the flexible extended warranty cannot be resumed once it isdiscontinued. In some instances, appliance analyzer 2214 may requirethat extended coverage begins at the end of a warranty originallyprovided with the appliances 2230-2238 (e.g., a base warranty).

Thus, at 2604, appliance analyzer 2214 may determine expected basewarranty expiration dates for the plurality of appliances 2230-2238, forexample, based on the age of the appliances 2230-2238, as determined instep 2596 mentioned above. In response to determining that the currentdate is later than the expected warranty expiration date for aparticular appliance 2230-2238, appliance analyzer 2214 may recommendcorresponding extended warranty coverage for that appliance 2230-2238.

At 2606, appliance analyzer 2214 preferably analyzes operatingparameters of refrigerator 2230 to determine whether a policyholdermight be interested in purchasing food spoilage protection insuranceplan. For instance, appliance analyzer 2214 may detect performancedegradation of refrigerator 2230 upon either it's past operatingperformance efficiency and/or its operating performance falling outsideof threshold values prescribed for it by a manufacturer. In response,appliance analyzer 2214 may recommend a food spoilage protection plan inaddition to recommended repairs. A food spoilage protection product maytake the form of a flexible duration. For instance, such plan mayreimburse up to $300 per claim on three-year plan and/or up to $500 perclaim on five-year plans for incurred spoilage losses. In an alternativeembodiment, appliance analyzer 2214 may recommend food spoilageprotection plan in response to detecting frequently occurring poweroutages.

At 2608, policy analyzer 2216 preferably automatically generates acomprehensive set of appliance insurance product recommendations basedon the analysis performed at steps 2594-2606. In an embodiment of thepresent disclosure, policy analyzer 2216 may be configured to determinea multiple product discount value, which can apply to combinations ofmultiple insurance products and/or combinations of multiple appliances.

At 2610, policy analyzer 2216 preferably provides a notificationindicating suggested appliance insurance product recommendations. It isto be appreciated that policy analyzer 2216 may be configured toelectronically deliver all notifications regarding recommended insuranceproducts or services. The notification can be anything that advises apolicy holder, device, or computer system of the suggested changes,including but not limited to, a display of text on a local displayscreen, a message in an email sent to a local or remote computer, a textmessage, a communication to a remote computer system. The electronicdelivery may include integration of notification functionalities intosocial networking services (e.g., via Facebook, Twitter, and the like).It is to be also understood and appreciated that policy analyzer 2216may be configured and operational to integrate with policy holder'scommunicative computing devices (e.g., smart phones (via an app),computers, tablets, smart TV's, vehicle communication systems, kitchencommunication systems, etc.) for sending such notifications regardinginsurance product recommendations. In an embodiment of the presentdisclosure, each notification may include, but not limited to, arecommendation to perform insurance related repairs based on thedetermined repair needs, a recommendation of one or more vendors toperform insurance related repairs based on the determined repair needs,additional insurance products and services, and the like. Additionally,policy analyzer 2216 may save the aforementioned recommendations in theinsurance server's 2012 storage component. These recommendations maythen be automatically communicated to the policy holder and/or reflectedin the policy holder's next insurance billing statement.

FIG. 24 shows, in the form of a flow chart, exemplary operational stepsof the dwelling analyzer 2212. Before turning to description of FIG. 24, it is noted that the flow diagram shown therein is described, by wayof example, with reference to components shown in FIGS. 11-13 , althoughthese operational steps may be carried out in any system and are notlimited to the scenario shown in the aforementioned figures.Additionally, the flow diagram in FIG. 24 shows an example in whichoperational steps are carried out in a particular order, as indicated bythe lines connecting the blocks, but the various steps shown in thesediagrams can be performed in any order, or in any combination orsub-combination.

In an embodiment of the present disclosure, exemplary operational stepsdescribed below may be carried out by the dwelling analyzer 2212 inorder to monitor the progress of a dwelling improvement project based oncaptured informatics sensor data. It is noted that the dwellingimprovement project may comprise dwelling repairs relating to damageassociated with a portion of the dwelling, such as a roof, windows,chimney, and the like. In addition, the dwelling improvement project maycomprise a remodeling project (i.e., replacing exterior siding,replacing an entry door, extending the heating and air conditioning,improving wiring and lighting, and the like) associated with thedwelling 2200.

With reference to FIG. 24 , at 2632, dwelling analyzer 2212 preferablyreceives specifications related to the dwelling improvement project, forexample, from computing device 2006. In an embodiment of the presentdisclosure, the specifications document may include one or morerequirements related to the dwelling improvement project. Theserequirements may identify, for instance, dwelling modification needs,dwelling maintenance needs, dwelling repair needs, and the like.Dwelling modifications needs may include minor or major modifications toany portion of the dwelling 2200 to improve safety, accessibility and/orthe quality of life. Dwelling modifications may include, but are notlimited to, replacing door handles or faucets, installing carpeting,modifying sinks or cabinets, and the like. Another example of this couldbe that a combustible material is too close to a heating source and hasa risk of starting a fire. Dwelling maintenance may include, but is notlimited to, changing furnace and/or air conditioner filters andreplacing appliances, such as air conditioners, garbage disposals,washers and dryers. Dwelling repair needs can include, but are notlimited to, repairing stairs, roofs, railings, and the like. Theaforementioned specifications may further include information indicativeof a degree of damage associated with the dwelling 2200, repairoperating procedures, the cost of the required services, such asmaterial and installation expenses.

In an embodiment of the present disclosure, the specifications mayinclude information related to an insurance policy associated with thedwelling 2200. If a specific insurance policy is identified, dwellinganalyzer 2212 may retrieve more detailed information from one or moredata storage devices (not shown in FIG. 3 ), which may becommunicatively coupled to server 2012 operated by an insurance company.Dwelling analyzer 2212 may utilize the retrieved data to determine whichof the repair/modification needs listed in the specifications documentwill be covered by the corresponding insurance policy. The insurancecompany may also include information related to an insurance policyassociated with the dwelling 2200 to determine if it wants to make thedwelling modification needs, dwelling maintenance needs, dwelling repairneeds, and the like conditions for whether it wants to provide insuranceto the insured, whether it wants to continue to provide insurance to theinsured, or whether it wants to make the modification/maintenance/repairneeds a condition for renewal or new issue of the policy at the dwelling2200.

At 2634, dwelling analyzer 2212 preferably collects data from sensors2004. In an embodiment of the present disclosure, this step may involvecomputing device 2006 periodically contacting (via network 2000), atprescribed time intervals, data analyzer component 2218 running onserver 2012 to send accumulated data. In an alternative embodiment,contact between the dwelling computing device 2006 and dwelling analyzer2212 may be initiated when the dwelling analyzer 2212 contacts thedwelling computing device 2006. Following the initial contact, dwellinganalyzer 2212 may receive data from the dwelling computing device 2006.It is to be understood data packets collected from sensors 2004 can beaggregated in dwelling computing device 2006 and send as an aggregatedpacket to dwelling analyzer 2212 for subsequent analysis.

In addition, at 2634, dwelling analyzer 2212 preferably processes theinformatics data collected by a plurality of sensors 2004 to assessvarious conditions indicative of a status of the dwelling improvementproject. In various embodiments of the present disclosure, the pluralityof sensors 2004 measuring and/or collecting informatics data may includeone or more of image sensors, structural sensors, temperature sensors,humidity sensors, environmental sensors, and so on. As previouslyindicated, upon the dwelling improvement project commencement, dwellinganalyzer 2212 may conduct a daily analysis to monitor progress and/or toverify compliance with the project specifications, as described below.

In another non-limiting embodiment, sensors can determine if recoverabledepreciation in a claim for a covered loss can be provided to theinsured. An example of how this could occur is a sensor 2004 can sendnotification to dwelling analyzer 2212 the insured has replaced,repaired or maintained an item in question with like kind and quality oritem(s) of similar quality and usefulness. When this happens, theinsurance company is notified and can provide the insured recoverabledepreciation.

At 2636, dwelling analyzer 2212 preferably identifies the most recentrepairs/modifications based on the latest informatics data. In anembodiment of the present disclosure, dwelling analyzer 2212 mayperiodically take images (snapshots) of one or more portions of thedwelling 2200 requiring repairs, modifications, and the like. Forexample, dwelling analyzer 2212 may determine whether an entry door hasbeen replaced by comparing the latest snapshot capturing an entry doorwith respective older snapshots. As another non-limiting example, thisstep may further involve monitoring structural condition of the dwelling2200. For instance, dwelling analyzer 2212 may identify one or morestructural changes by analyzing the condition of the wall structure,floor structure, ceiling structure and roof structure of the dwelling2200. In one implementation, dwelling analyzer 2212 may perform thisidentification by comparing latest measurements of the slope of afloor/wall/ceiling with previously taken measurements. Again, thisinformation can be used to assist in claims settlement after a claim inregards to recoverable depreciation in a claim for a covered loss.

The insurance company can use the information from dwelling analyzer2212 for whether the insured is or has made changes or updates to thedwelling 2200 and use this information for things like underwritingacceptability, pricing, and as a condition for renewal of the policy at2638, dwelling analyzer 2212 may determine whether the one or moreidentified changes related to the one or more conditions associated withthe dwelling improvement project satisfy one or more predefinedrequirements. In other words, in this step dwelling analyzer 2212 maydetermine whether the performed repairs/modifications meet therequirements included in the specification document (received at 2632).For example, dwelling analyzer 2212 may determine whether appropriatematerials were used to perform repairs. In another example, if one ofthe requirements listed in the specifications necessitated a repair of abroken window, dwelling analyzer 2212 may determine whether the brokenwindow has been replaced. As described above, this could assist todetermine if recoverable depreciation in a claim for a covered loss canbe provided to the insured.

In response to determining that the performed repairs/modificationscomply with the requirements (step 2638, yes branch), at 2640, dwellinganalyzer 2212 preferably checks other portions of the dwelling 2200(including utility systems) within the dwelling 2200 that may have beenaffected by the performed repairs/modifications. The utility systems,may include, but are not limited to, electrical wiring, plumbing,heating, ventilation, and the like. For instance, if dwelling analyzer2212 determines that one of the plumbing appliances was recentlyreplaced, dwelling analyzer 2212 may measure and/or record the amount ofwater pressure present in the dwelling's 2200 water supply system and/orany changes in that pressure. In some dwellings 2200 plumbing systemsmay be designed to withstand a certain amount of pressure, and if thepressure rises above that amount, the plumbing system may be at risk forleaking, bursting, or other failure. Thus, at 2640, dwelling analyzer2212 may verify that performed repairs will not cause future damage tothe dwelling 2200. Similarly, if any of the kitchen appliances have beenreplaced during the dwelling improvement project, dwelling analyzer 2212may assess the condition of the dwelling's electrical system. Electricalsystem readings could be used to determine if the voltage ispersistently too high, or too low, or if the voltage frequently dropsand/or spikes. Such conditions may suggest that the dwelling 2200 is atrisk for fire.

The insurance company can use the information from dwelling analyzer2212 for whether the insured is or has made changes or updates to thedwelling 2200 and use this information for things like underwritingacceptability, pricing, and as a condition for renewal of the policy. Ifthe assessment performed at 2640 detects any additional problems (step2642, yes branch), dwelling analyzer 2212 may determine next (at 2643)whether the detected issues are covered by the insurance policyassociated with the dwelling 2200. This step may further involvedetermining whether the detected issues require immediate repairs and/ortemporary repairs to mitigate or prevent further damage to the dwelling2200. If so, dwelling analyzer 2212 may provide a correspondingnotification, at 2646, as described below. According to an embodiment ofthe present disclosure, dwelling analyzer 2212 preferably amends thespecification document related to the dwelling improvement project toinclude newly identified repair requirements if the repairs are coveredby the corresponding insurance policy.

In response to detecting no additional problems/issues (step 2642, nobranch), at 2644, dwelling analyzer 2212 may determine next whether thedwelling improvement project has been completed. In an embodiment of thepresent disclosure, dwelling analyzer 2212 may verify that allrequirements included in the specification have been satisfied. If thedwelling improvement project has not been completed (step 2644, nobranch), dwelling analyzer 2212 may return back to step 2634 in order toreceive and process next set of collected informatics data after a setperiod of time. In response to determining that the dwelling improvementproject has been completed (step 2644, yes branch), dwelling analyzer2212 may provide a corresponding status notification.

As mentioned above, at 2646, dwelling analyzer 2212 preferably providesa notification indicating a status of the dwelling improvement projectbased on captured informatics sensor data. It is to be appreciated thatdwelling analyzer 2212 may be configured to electronically deliver allnotifications. The notification can be anything that advises a policyholder, device, or computer system of the current status of the dwellingimprovement project, including but not limited to, a display of text ona local display screen, a message in an email sent to a local or remotecomputer, a text message, a communication to a remote computer system.It is to be also understood and appreciated that dwelling analyzer 2212may be configured and operational to integrate with policy holder'scommunicative computing devices (e.g., smart phones (via an app),computers, tablets, smart TV's, vehicle communication systems, kitchencommunication systems, etc.) for sending such notifications regardingdwelling repairs/modifications. In an embodiment of the presentdisclosure, if dwelling analyzer 2212 determines that performed repairsdo not comply with the requirements (step 2638, no branch), thegenerated notification may indicate that one or more requirements hasnot been satisfied by the repairs. If dwelling analyzer 2212 detects anyissues/damage that may have been caused by the performedrepairs/modifications (step 2642, no branch), the generated notificationmay identify the detected problems and may further indicate whethersuggested repairs are covered by the insurance policy associated withthe dwelling 2200. If at step 2644 (yes branch) dwelling analyzer 2212determines that the improvement project has been completed, thenotification generated at 2646 may include a status indicative of thesuccessful completion of the project. In various embodiments, thenotification generated by dwelling analyzer 2212 may include one or moreimages of one or more portions of the dwelling 2200. As described above,the information collected by the dwelling analyzer 2212 can determinewhether the repairs to the dwelling 2200 were made and can determine ifrecoverable depreciation in a claim for a covered loss can be providedto the insured.

FIG. 25 shows, in the form of a flow chart, exemplary operational steps2660 of the dwelling analyzer 2212. Before turning to description ofFIG. 25 , it is noted that the flow diagram shown therein is described,by way of example, with reference to components shown in FIGS. 11-13 ,although these operational steps may be carried out in any system andare not limited to the scenario shown in the aforementioned figures.Additionally, the flow diagram in FIG. 25 shows an example in whichoperational steps are carried out in a particular order, as indicated bythe lines connecting the blocks, but the various steps shown in thesediagrams can be performed in any order, or in any combination orsub-combination.

With reference to FIG. 25 , at 2662, dwelling analyzer 2212 preferablycollects data from sensors 2004. In an embodiment of the presentdisclosure, this step may involve computing device 2006 periodicallycontacting (via network 2000), at prescribed time intervals, dataanalyzer component 2218 running on server 2012 to send accumulated data.In an alternative embodiment, contact between the dwelling computingdevice 2006 and dwelling analyzer 2212 may be initiated when thedwelling analyzer 2212 contacts the dwelling computing device 2006.Following the initial contact, dwelling analyzer 2212 may receive datafrom the dwelling computing device 2006. It is to be understood datapackets collected from sensors 2004 can be aggregated in dwellingcomputing device 2006 and send as an aggregated packet to dwellinganalyzer 2212 for subsequent analysis.

At 2664, dwelling analyzer 2212 preferably processes the informaticsdata collected by a plurality of sensors 2004 to assess environmentalconditions related to the dwelling 2200. Environmental conditions mayinclude, but are not limited to: temperature conditions, windconditions, air quality present in the dwelling 2200, humidity presentin the dwelling 2200, and so forth. In various embodiments of thepresent disclosure, the plurality of sensors 2004 measuring and/orcollecting environmental informatics data may include one or more oftemperature sensors, humidity sensors, sound sensors, wind speedsensors, environmental sensors, and so on.

As previously indicated, dwelling analyzer 2212 may perform a post hocanalysis. For example, if a hurricane strikes the area in which thedwelling 2200 is located, dwelling analyzer 2212 may analyze the windspeed, temperature, and movement at various points in time. If thedwelling 2200 is damaged, it may be possible to determine, based on theanalysis of collected informatics data, the actual mechanism by whichthe dwelling 2200 was damaged, and/or how long the dwelling 2200withstood the hurricane-force winds. Various types of informatics datamay be analyzed by dwelling analyzer 2212 to learn, in some detail,about the event that damaged the dwelling 2200. This analysis may beused by dwelling analyzer 2212 to estimate future risks.

In addition to performing a post hoc analysis, dwelling analyzer 2212may be configured to analyze information about environmental conditionsthat are present at the dwelling 2200 in advance of any actual damage.For example, dwelling analyzer 2212 may analyze the wind speed at thedwelling 2200, in order to get a picture of the average wind speed overa period of few months. If dwelling analyzer 2212 detects a trend towarda higher wind speed, this fact may suggest an increased likelihood ofdamage (e.g., trees may be more likely to fall in the presence of highermagnitude winds). As another example, dwelling analyzer 2212 couldanalyze humidity readings, where a trend toward higher humidity mayindicate an increased likelihood of mold damage.

In an embodiment of the present disclosure, dwelling analyzer 2212 maycollect data from more than one dwelling in a geographic area todetermine the general level of risk in the area. For example, dwellinganalyzer 2212 may analyze the data from approximately ten houses in aparticular geographic location to determine that average wind speed hasbeen increasing over the past few years. As another example, dwellinganalyzer 2212 may determine whether a particular geographic area inwhich the dwelling 2200 is located is prone to earthquakes based onrecent seismic activity measured by various environmental sensors I 02.An insurance company could use this information to mitigate futureloses, as described below.

At 2666, based on data collected from sensors I 02 regarding dwelling2200, dwelling analyzer 2212 preferably conducts an analysis todetermine a structural condition of the dwelling 2200. For example,dwelling analyzer 2212 may determine whether harsh environmentalconditions, such as hurricane, storm surge, earthquake, volcano,landslide, and the like, have affected structural integrity of thedwelling 2200. In addition to the above, some geographic regionscommonly experience problems that cannot only be a nuisance to thoseliving in the residence, but which can also destroy the structuralintegrity of the dwelling structure itself. For example, termites arejust one type of insect that are known to infest and damage homes. Thus,dwelling analyzer 2212 may conduct an analysis to detect dangerousinsect infestations within the dwelling 2200 structure. As yet anothernon-limiting example, in this step dwelling analyzer 2212 may detect ahole in the roof of the dwelling 2200 requiring immediate repair. Ingeneral, at 2666, dwelling analyzer 2212 may analyze the collected datato determine whether dwelling 2200 and/or any of its components satisfystructural soundness requirements.

At 2668, dwelling analyzer 2212 preferably assesses exposure of thedwelling 2200, for example, by identifying risks associated with one ormore perils. As used herein, the term “peril” refers to a cause of loss.By way of example, such perils (or perilous events) may include anatural disaster (e.g., a tornado, a hurricane, an earthquake, a flood,etc.), a manmade disaster (e.g. a release of hazardous material, gaspipe explosion, arson, etc.), and the like. In an embodiment of thepresent disclosure, dwelling analyzer 2212 preferably evaluates levelsof exposure for each peril based on observed and/or historicalinformatics data. As an illustrative example, dwelling analyzer 2212 maydetermine estimated likelihood that a specified peril (e.g., a tornado)may occur in a specified geographical zone to cause a specified degreeof damage (e.g., $10 million), based on environmental conditionsanalyzed by the dwelling analyzer 2212 at 2664.

Next, at 2670, dwelling analyzer 2212 preferably generates a mitigationreport, which may include various risk mitigation options associatedwith the one or more perils identified at 2668. The mitigation reportmay further include a current risk assessment, a future risk assessment,and repair recommendations if, for example, dwelling analyzer 2212 hasdetermined (at 2666) that structural integrity of the dwelling 2200 hadbeen compromised or might be compromised in the future. For instance, ifdwelling analyzer 2212 has detected a hole in the roof of the dwelling2200, dwelling analyzer 2212 may recommend an immediate repair. Asanother risk mitigation option, based on the analysis performed at2664-2668, dwelling analyzer 2212 may recommend constructing areinforced section of the dwelling 2200 capable of withstanding one ormore environmental conditions associated with the perceived exposure ofthe dwelling. For instance, if dwelling analyzer 2212 has determinedthat a likelihood of tornado in the general vicinity of dwelling 2200has increased then dwelling analyzer 2212 may recommend building a “saferoom” within the dwelling 2200. A safe room may comprise a hardenedstructure specifically designed to provide protection to the dwelling2200 occupants in extreme weather events, including tornadoes andhurricanes. Moreover, based on the analysis of the informatics data(i.e., wind analysis) dwelling analyzer 2212 may provide guidance tovarious third parties, such as but not limited to, architects,engineers, building officials, local officials, emergency managers,independent contractors, and prospective safe room owners, related tosafe room construction options. Advantageously, the occupants of a saferoom built in accordance with dwelling analyzer's 2212 guidance may havea very high probability of being protected from injury or death. Thus,dwelling analyzer 2212 may provide proactive and real-time management ofinsurance loss minimization.

Optionally, at 2672, dwelling analyzer 2212 may conduct a cost-benefitanalysis related to various risk mitigation options. In an embodiment ofthe present disclosure, dwelling analyzer 2212 may perform evaluation ofthe probable maximum loss (“PML”) corresponding to the dwelling 2200.Determining the PML for a property is conventionally treated as anevaluation of the costs likely to be incurred in response to aparticular loss event. For example, this valuation is typicallydetermined simply as the replacement cost of restoring a dwelling in theevent of a flood or rebuilding a structure following a fire. It is notedthat other types of analysis related to exposure of the dwelling 2200may be made by the dwelling analyzer 2212 at 2668. In addition, dwellinganalyzer 2212 may automatically facilitate and/or determine the mostcost efficient repair options, if immediate repairs are needed. Forinstance, dwelling analyzer 2212 may identify one or more vendorscapable of performing the repairs related to the one or more riskmitigation options in the most-cost effective manner.

At 2674, dwelling analyzer 2212 may provide captured informatics data tothird parties to mitigate future insurance claims. Captured informaticsdata my include, but not limited to, historic and/or real timetemperature measurements, wind measurements, air quality measurements,humidity measurements, and the like. Third parties that may be involvedin mitigating risks associated with future insurance claims may include,but not limited to, one or more vendors selected to perform the repairsrelated to the one or more risk mitigation options, other insurancecompanies (if, for example, reinsurance is identified as a riskmitigating option), various governmental entities that might providefunding/rebates for the performed repairs. For instance, occupants ofthe dwelling 2200 may be interested in applying for a safe room rebateprogram. In this case, dwelling analyzer 2212 may provide collectedand/or analyzed data to Federal Emergency Management Agency (FEMA), forexample, if FEMA is the government entity providing such rebates. In anembodiment of the present disclosure, dwelling analyzer 2212 may beintegrated with one or more third party information systems, such asNational Emergency Management Information System, for exchanginginformation.

At 2676, dwelling analyzer 2212 may optionally provide the generatedmitigation report to the aforementioned third parties. As previouslyindicated the mitigation report may include various risk mitigationoptions (such as repair recommendations) associated with the one or moreperils identified at 2668, a current risk assessment, a future riskassessment, as well as cost benefit analysis and the damage historyassociated with the dwelling 2200. The mitigation report may furtherinclude additional guidance related to, for example, recommended repairsbased on the determined dwelling's 2200 structural condition. It is tobe also understood and appreciated that the insurance server I 06 may beconfigured and operational to integrate with various third partyinformation systems for sending such mitigation report and otherinformation regarding mitigation of future insurance claims.

With reference to the process 2690 of FIG. 26 , at 2692, dwellinganalyzer 2212 preferably collects data from sensors 2004. In anembodiment of the present disclosure, this step may involve computingdevice 2006 periodically contacting (via network 2000), at prescribedtime intervals, data analyzer component 2218 running on server 2012 tosend accumulated data. In an alternative embodiment, contact between thedwelling computing device 2006 and dwelling analyzer 2212 may beinitiated when the dwelling analyzer 2212 contacts the dwellingcomputing device 2006. Following the initial contact, dwelling analyzer2212 may receive data from the dwelling computing device 2006. It is tobe understood data packets collected from sensors 2004 can be aggregatedin dwelling computing device 2006 and sent as an aggregated packet todwelling analyzer 2212 for subsequent analysis.

At 2694, dwelling analyzer 2212 preferably processes the received data.For example, dwelling analyzer 2212 may include a parser configured toparse the aggregated packet and classify the received data based on, forexample, type of sensor employed to collect a particular subset of thereceived data. Dwelling analyzer 2212 may create a data structure foreach classification. This step may further involve identifying a policyassociated with dwelling 2200 from which the received data is collected.

At 2696, dwelling analyzer 2212 preferably periodically monitors one ormore utility systems associated with the dwelling based on the receivedinformatics data. The monitored utility systems may include but are notlimited to electrical wiring system, plumbing system, central heatingsystem, and the like. The monitored utility systems may be incorporatedinto the structure of dwelling 2200. For example, electrical systemsensors may be connected to various points in the dwelling's 2200electrical system to measure voltage. Dwelling analyzer 2212 may usereadings from the electrical system sensors to determine if the voltageis persistently too high, or too low, or if the voltage frequently dropsand/or spikes. Such conditions may suggest that the dwelling 2200 is atrisk for fire. As another non-limiting example, this step may furtherinvolve periodically checking informatics data related to the componentsof the dwelling's 2200 plumbing system to detect any water leaks.Generally, water leaks could cause damage to some parts of thedwelling's 2200 structure. Damages to the dwelling structural elementscould cause the dwelling 2200 to deteriorate faster, collapse, and causeinjuries to its occupants.

At 2698, dwelling analyzer 2212 preferably processes the informaticsdata collected by a plurality of sensors 2004 to assess environmentalconditions related to the dwelling 2200. Environmental conditions mayinclude, but are not limited to: temperature conditions, windconditions, air quality present in the dwelling 2200, humidity presentin the dwelling 2200, and so forth. In various embodiments of thepresent disclosure, the plurality of sensors 2004 measuring and/orcollecting environmental informatics data may include one or more oftemperature sensors, humidity sensors, sound sensors, wind speedsensors, environmental sensors, and so on. In an embodiment of thepresent disclosure, dwelling analyzer 2212 may analyze the collecteddata to detect an occurrence of a natural peril event based on thereceived informatics data. As used herein, the term “peril” refers to acause of loss. By way of example, such perils (or peril events) mayinclude, but are not limited to a tornado, a hurricane, an earthquake, aflood, and the like.

At 2700, in response to detecting an occurrence of one or more naturalperil events (step 2698, yes branch), dwelling analyzer 2212 preferablyconducts an analysis to identify certain immediately needed repairs tothe structure of a dwelling 2200. For example, this step may involvemonitoring structural condition of the dwelling 2200. As a result,dwelling analyzer 2212 may detect, for example, a hole in the roof ofdwelling 2200 (via one or more sensors 2004), requiring immediaterepair. As another example, an environmental sensor may have detected agas leak or any contaminant adverse to human health. As yet anotherexample, dwelling temperature analysis may have indicated amalfunctioning cooling/heating system. In general, any dwellingcondition caused by the natural peril event that affects the residents'health or safety may be considered by dwelling analyzer 2212 asrequiring an immediate repair.

If dwelling analyzer 2212 does not detect an occurrence of any naturalperil events (step 2698, no branch), at 2702, dwelling analyzer 2212preferably conducts an analysis to identify certain preventive repairsto the structure of a dwelling 2200. For example, based upon certainanalysis, dwelling analyzer 2212 may recommend preventive maintenance tothe roof a dwelling 2200 (e.g., detection of wind, moisture, improperroof slope line, etc.). For instance, dwelling analyzer 2212 mayidentify one or more structural changes by analyzing the condition ofthe wall structure, floor structure, ceiling structure and roofstructure of the dwelling 2200. In one implementation, dwelling analyzer2212 may perform this identification by comparing latest measurements ofthe slope of a floor/wall/ceiling with previously taken measurements. Asanother example, based upon analysis of a plumbing system, dwellinganalyzer 2212 may have detected long-term stress on pipes. In order toprevent water leaks, dwelling analyzer 2212 may recommend reducing waterpressure (e.g., by installing a water softener) to prevent futureplumbing leaks. As another example, based upon, for example, an air flowanalysis, dwelling analyzer 2212 may have detected that damaged framesand/or dividers allow air leaks into dwelling 2200. Thus, dwellinganalyzer 2212 may make recommendations with regards to windowreplacement/repair needs.

According to an embodiment of the present disclosure, at 2704, dwellinganalyzer 2212 may generate a maintenance profile corresponding to thedwelling 2200 based on the received informatics data and based on theanalysis performed at 2696-2702. The maintenance profile may includeboth urgent and essential repair needs. For example, the generatedmaintenance profile may indicate that electrical wiring system is so oldthat it needs an immediate upgrade. As another example, the maintenanceprofile may point out that gas heating boiler has not received itsannual service. In addition, the maintenance profile may include forwardmaintenance plans, for instance, for the next five to seven years,establishing, for example, the date of the next re-painting job, thedate of the next windows replacement job, and the like. Furthermore, thegenerated maintenance profile may include detailed information about allnecessary and planned repairs.

In an embodiment of the present disclosure, upon generation of themaintenance profile, at 2706, dwelling analyzer 2212 may store thegenerated maintenance profile in the claim system repository 2226 (whichis shown, in FIG. 13 , as being part of, or used by, insurance server2012). The claim system repository 2226 may comprise a database or anyother suitable storage component. For example, the suitable storagecomponent may comprise, or may otherwise make use of, magnetic oroptical disks, volatile random-access memory, non-volatile random-accessmemory or any other type of storage device.

FIG. 27 is a flow diagram of operational steps of the maintenancemanager module of FIG. 13 in accordance with an illustrated embodiment.At 2722, maintenance manager 2220 preferably retrieves the maintenanceprofile corresponding to the dwelling 2200 generated by the dwellinganalyzer 2212 from the insurance server's 2012 claim system repository2226. In an alternative embodiment of the present disclosure, this stepmay involve the maintenance manager 2220 receiving the maintenanceprofile directly from the dwelling analyzer 2212. Next, maintenancemanager 2220 preferably maps the received/retrieved data to a particularinsurance policy associated with the dwelling 2200.

Next, at 2724, maintenance manager 2220 preferably analyzes historicalinformation related to maintenance of the dwelling 2200. For example,maintenance manager 2220 may determine a total number of completedrepairs over a predetermined period of time (e.g., one year). As anotherexample, maintenance manager 2220 may analyze historical data todetermine average annual cost of repairs associated with the dwelling2200. The analyzed historical data may also help maintenance manager2220 to determine the effectiveness of previously performed maintenancerelated repairs. The foregoing examples of historical data areillustrative only and are not intended to be in any way limiting. It isnoted that historical information described herein may be collected bydata analysis module 2210 and may be stored at the insurance server's2012 claim system repository 2226.

At 2726, maintenance manager 2220 analyzes the insurance policyassociated with the dwelling 2200 to further assess dwelling coverage.Typically, a standard home insurance policy does not cover issuesrelated to a lack of maintenance. For example, if a plumbing leak thatwas left unfixed caused mold to grow in the interior walls of dwelling2200 mold removal and remediation would not be covered by a standardinsurance policy. Generally, standard home insurance policy onlyprotects a policyholder from damage caused by covered natural perilssuch as wind, hail, lightening, fire and the like. Keeping a dwellingwell maintained and safe for others is policyholder's responsibility anda home insurance company may decline coverage for maintenance relatedclaims. However, additional coverage may be purchased by a policyholder. For example, an insurance policy associated with the dwelling2200 may include roof replacement cost coverage.

Optionally, at 2728, maintenance manager 2220 may evaluate the list ofall urgent and essential repairs that may be contained in themaintenance profile to prioritize such repairs based on, for example,the insurance policy associated with the dwelling 2200. For instance,maintenance manager 2220 may establish, for example, the date of thenext re-painting job, the date of the next windows replacement job, andthe like. According to an embodiment of the present disclosure,maintenance manager 2220 may set optimum times for major improvements inthe dwelling 2200, such as renovating the bathroom or kitchen orreplacing the plumbing. Advantageously, maintenance manager 2220 mayestimate optimum times for performing repairs/renovations by correlatingcaptured informatics sensor data related to the dwelling 2200 with thecorresponding insurance policy.

At 2730, maintenance manager 2220 preferably selects one or morepreferred maintenance/repair vendors. Maintenance/repair vendors areseparate entities, each with the capability to perform a particular typeof repair. For example, one vendor may specialize in insurancerestoration work on roofing, siding, gutters and windows. Another vendormay have the capability to repair and fix the gas leak. Thus,maintenance manager 2220 may select one or more preferred vendors based,at least in part, on data collected from sensors 2004. In an embodimentof the present disclosure, the preferred vendors can have exclusivecapabilities, meaning that the capability to handle any one particularrepair by one vendor is not shared by the remaining vendors. In analternative embodiment, the preferred vendors can have nonexclusivecapabilities, meaning that the capability to handle any one-repairservice by any one vendor is shared by one or more remaining vendors.Moreover, the capabilities of various vendors to handle the same type ofrepair may involve different technologies and charges (i.e., costs). Thepreferred vendor list may be stored, for example, in claim systemrepository 2226.

At 2732, maintenance manager 2220 may reconcile maintenance analyticsperformed at steps 2724 with the insurance policy associated with thedwelling 2200. For example, maintenance manager 2220 may recommendadditional coverage for some of the planned repairs included in themaintenance profile (i.e., roof replacement coverage, interior plumbingand drainage coverage, and the like). As another example, maintenancemanager 2220 may select a different vendor to perform specific repairsby reconciling vendors' estimated charges, fee structures, with coverageprovided by the insurance policy.

At 2734, maintenance manager 2220 may send a request to initiate a claimto an insurance company claim system (which is not shown in FIG. 13 ,but may be a part of, or used by, insurance server 2012). Such a requestmay be received on a device associated with the claim system, such asinsurance server 160, or any other device capable of receiving a requestfor the initiation of an insurance claim. The request sent bymaintenance manager 2220 to the claim system may include informationrelevant to maintenance/repair and/or insurance policy associated withthe dwelling 2200. For example, maintenance manager 2220 may beconfigured to provide insurance policy identification, maintenanceprofile, preferred vendor's identification and/or any other informationthat may be of use in initiating an insurance claim. All suchinformation is contemplated as within the scope of the presentdisclosure.

At 2736, maintenance manager 2220 preferably provides a claim statusnotification based on the request sent to the insurance company claimsystem (at 2734). It is to be appreciated that policy analyzer 2216 mayalso be configured to electronically deliver all notifications regardingplanned and/or recommended repairs. The notification can be anythingthat advises a policy holder, device, or computer system of the dwellingmaintenance and claim initiation related activities, including but notlimited to, a display of text on a local display screen, a message in anemail sent to a local or remote computer, a text message, acommunication to a remote computer system. It is to be also understoodand appreciated that maintenance manager 2220 may be configured andoperational to integrate with policyholder's communicative computingdevices (e.g., smart phones (via an app), computers, tablets, smartTV's, vehicle communication systems, kitchen communication systems,etc.) for sending such notifications. In an embodiment of the presentdisclosure, each notification may include, but not limited to,information related to immediate repair needs, recommended time periodfor performing major dwelling improvements, information related to oneor more preferred maintenance/repair vendors (for example, selected at2730), information related to a claim status, and the like.Additionally, maintenance manager 2220 may save the aforementioned claimstatus and/or repair recommendations in the insurance server's 2012claim system repository 2226.

With reference now to FIG. 28 , shown is insurance server 2012 coupledto computing device 2006 for receiving data from sensors 2004 preferablyrelating to a dwelling 2200 in accordance with the above description. Inaddition to being coupled to dwelling computing device 2006, insuranceserver 2012 is also shown coupled to vehicle telematics device 2752,external computing devices/servers 2760 and a workplace device(s) 2754.Network 2000, and links 109 thereof (FIG. 11 ), preferably couple server2012 to each of the aforementioned components (e.g., computing device2006, workplace devices 2754, telematics device 2752 and externalcomputing devices 2760).

With respect to telematics device 2752, it is preferably coupled to oneor more user vehicles 2758 for receiving telematics and relateddata/information from each coupled vehicle 2758. The configuration,functionality and operability of telematics device 2752 is described incommonly assigned U.S. Patent Application Ser. No. 61/881,335 which isincorporated by reference in its entirety herein. It is to be understoodand appreciated, telematics device 2752 provides user vehicle relatedinformation to be aggregated by insurance server 2012 as discussedfurther below.

With regards to external computing devices 2760, each is preferablyassociated with a service provider relating to a user's dwelling,vehicle 2758 and/or health condition. For instance, they may include(but are not limited to) emergency responders (e.g., police, fire,medical, alarm monitoring services, etc.), utility companies (e.g.,power, cable (phone, internet, television), water), service providers(e.g., home appliance and automotive service providers),information/news providers (e.g., weather and traffic reports and othernews items) and other like service/information/data providers.

In one aspect of the present disclosure, insurance server 2012 may becoupled to one or more workplace devices 2754 for evaluatingpolicyholder's safety in the workplace. Safety in the workplace mayinclude perils beyond driving, including (but not limited to)environmental conditions, physical stress and strain, and dangerousequipment. Sensors located in the policyholder's workplace may, forexample, identify dangerous scenarios, including environmentalconditions, worker behaviors, worker schedule, use or lack of use ofproper safety equipment, and interactions with dangerous machines,substances or areas. Workplace devices may include (but not limited to)wearable devices 2755 which may be worn by the policyholder, deviceslocated on machinery 2756, equipment 2757, objects 2759, and distributedaround workplace environment. Workplace devices 2754 are preferablyconfigured to take a variety of measurements. For example, motiondetectors worn by a policyholder may measure body motion as thepolicyholder moves around and carries out various tasks at work.Multiple motion sensors may be worn on different body parts to obtaindetailed body movement information. Motion sensors may monitor speed,acceleration, position, rotation, and other characteristics of body andappendage motion. There are sensors available in the marketplace fordetermining the body posture of employees, particularly while liftingheavy objects. Chronic and acute back injuries are often the result oflifting objects using an improper lifting behavior, and can lead to highvalued insurance claims. Pressure sensors embedded in the footwear of apolicyholder or located on the floor of workplace also could provideinformation on the ergonomics, such as weight and weight distributionover different parts of policyholder's body. Workplace devices 2754 mayinclude many other types of sensors which may be used to gaininformation about the work habits of the policyholder.

FIG. 29 shows, in the form of a flow chart, exemplary operational stepsof the data analyzer 2218. Before turning to descriptions of FIG. 29 ,it is noted that the flow diagram shown therein is described, by way ofexample, with reference to components shown in FIGS. 11-13 and 28 ,although these operational steps may be carried out in any system andare not limited to the scenario shown in the aforementioned figures.Additionally, the flow diagram in FIG. 29 shows examples in whichoperational steps are carried out in a particular order, as indicated bythe lines connecting the blocks, but the various steps shown in thesediagrams can be performed in any order, or in any combination orsub-combination.

With reference to FIG. 29 , at 2792, data analyzer 2218 preferablycollects data related to a policyholder's dwelling 2200 from sensors2004 placed at various locations in and around the dwelling 2200. In anembodiment of the present disclosure, this step may involve computingdevice 2006 periodically contacting (via network 2000), at prescribedtime intervals, data analyzer component 2218 running on server 2012 tosend accumulated data. In an alternative embodiment, contact between thedwelling computing device 2006 and data analyzer 2218 may be initiatedwhen the data analyzer 2218 contacts the dwelling computing device 2006.Following the initial contact, data analyzer 2218 may receive data fromthe dwelling computing device 2006. It is to be understood data packetscollected from sensors 2004 can be aggregated in dwelling computingdevice 2006 and sent as an aggregated packet to data analyzer 2218 forsubsequent analysis.

At 2794, data analyzer 2218 preferably collects telematics data from thetelematics device(s) 2752 (shown in FIG. 28 ) that are preferablycoupled to one or more policyholder vehicles 2758. As previouslyindicated, the telematics device 2752 may be used to monitor a number ofaspects of the use of the motor vehicles 2758. For example, thetelematics device 2752 monitors the speed at which the vehicle istravelling. The telematics device 2752 may also able to send datarelated to braking habits of the policyholder (or another driveroperating the vehicles 2758) either using the GPS functionality or byusing an accelerometer or having one or more sensors connected to adeceleration detection device, for example. The telematics device 2752may also be configured and operable to detect the distance travelled andif the vehicle was driven for a long time period without a break. Inaddition, the times of the day that the vehicle 2758 is being driven canbe captured as night time driving is statistically more dangerous thanday time driving, especially weekend late night driving. According to anembodiment of the present disclosure, based on the data provided bytelematics devices 2752, the data analyzer 2218 may be able to determinewhen the vehicle 2758 turns without indicating, for example. In anyevent, the data from the telematics devices 2752 may be transmitted toan insurance server 2012 over a communication network 2000.

At 2796, data analyzer 2218 preferably collects data related to apolicyholder's health and wellness condition from, for example,aforementioned activity monitoring sensors 2004 placed at variouslocations in and around the dwelling 2200. This data may includeinformation related to policyholder's exercise, diet, habits, healthhistory and conditions, as well as other wellness factors. The dataanalyzer 2218 may use this data to calculate the policyholder's currentwellness state, which can be used to classify a pool of policyholdersaccording to degree of wellness. Furthermore, data analyzer 2218 can usethis classification level data to calculate premiums based on wellness.As a result, policyholders who maintain a higher state of wellnessrelative to other same age and gender policyholders can receive lowerpremiums. Policyholders with a lower wellness status can receive areward (such as a reduced premium) for improving their state ofwellness. According to embodiments of the present disclosure, dataanalyzer 2218 may be configured and operable to process a large amountof health and wellness data received at 2796.

At 2798, data analyzer 2218 preferably collects data from workplacedevices 2754 which may be used to gain information about the work habitsof the policyholder. This data may include a variety of measurementsdescribed above. In an embodiment of the present disclosure, dataanalyzer 2218 may utilize data gathered at 2798, for example, toidentify patterns and trends that could be used to reduce, throughprevention, the occupational risks of injury and death associated withpolicyholder's workplace.

With continuing reference to the gathering of data in step 2798, in anillustrated embodiment, an insurance company's Customer RelationshipManagement (CRM) tool/module may be operative to enable the insurancecompany to understand a policyholder better. For instance, the CRM toolis operative to determine the policyholder has a homeowner's policy, achecking account, a life insurance policy and an investment device.Since this policyholder has multiple lines of business with the company,it is determined the loss performance may be lower than anotherpolicyholder with a homeowners policy only. Additionally, the CRM may beoperative to determine the payment history for the policyholder. Thisinformation may be used to determine the policyholder's payment historyas a data layer for making rating, acceptability, and/or coveragedecisions.

With continuing reference to FIG. 29 , data analyzer 2218 preferablycollects data related to a policyholder's surrounding riskcharacteristics. These risk characteristics can be data layers about theinsured's risk in the area the insured lives. Examples of the risks thatcan be known about the insured are, but are not limited to, thehurricane risk, earthquake risk, flood risk, crime risk, wildfire risk,lightning risk, hail risk, and sinkhole risk. These risk factors can addto the information known about the insured and can be useful to thecompany for determining (and not to be understood to be limited to)pricing, acceptability, underwriting, and policy renewal.

Additionally, data analyzer 2218 preferably collects data related tounstructured data. Unstructured data refers to information that eitherdoes not have a pre-defined data model or is not organized in apredefined manner. Unstructured data is typically text heavy, but maycontain data like dates, numbers and facts. An example of the way aninsurance company could collect unstructured data is from social medialike Facebook and Twitter. For instance, a community in a high wildfirearea organizes wildfire prevention and mitigation efforts social mediacoordination efforts. The insurance company can monitor the social mediasites and may know that this community is organizing and utilizingwildfire loss mitigation techniques. This data layer could be used alongwith the other information about the policyholder for the insurancepolicy. Also, the insurance company may determine that this wildfirecommunity is not giving out the latest wildfire science information tothe community members. The insurance company provides the community withthe latest in wildfire science mitigation techniques.

It should be recognized the data from sensors 2004 and telematics device2752 may be utilized by data analyzer 2218 to determine a risk profileassociated with insured property 2200, a vehicle 408, and/or apolicyholder associated therewith. Such a risk profile could take theform of a “maintenance score” for a insured property or “driving score”with respect to a vehicle, as will be further described below.

For instance, data from an appliance sensor may be used to determinewhether the appliances within an insured property 2200 are maintained.If the appliances were maintained regularly within a particularinterval, then such maintenance would positively affect the maintenancescore. Conversely, if the appliances were not maintained regularly, thenthe maintenance score would be negatively affected.

In another instance, data from temperature and/or humidity sensors maybe used to determine whether an owner (or occupant) of an insuredproperty 2200 takes care to control the climate of an insured propertyin a responsible way. If the owner does control the climate in aresponsible way, then such behavior would positively affect themaintenance score, and vice versa.

In another instance, data from a motion sensor may be utilized todetermine whether or not there is responsible activity occurring in theinsured property 2200. For example, regular consistent steady stateactivity may indicate that an insured property is used solely as ahabitat whereas spikes in activity or frenetic activity may indicatethat an insured property is not being used solely as a habitat, but maybe being used in a manner that creates additional risks or disadvantagesfor the insured property.

Various method steps have been shown at 2792-2798. It should beappreciated that in some embodiments one or more of the steps 2792-2798may be combined into a single step. In some embodiments, one or more ofthe steps 2792-2798 may be changed in terms of order. In someembodiments, one or more steps may be omitted. In some embodiments, oneor more additional steps may be included. Also, the above embodimentsare not intended to be all inclusive. Moreover, data analyzer 2218 mayinclude a parser configured to parse, aggregate and classify thereceived data (at 2792-2798) based on, for example, type of sensoremployed to collect a particular subset of the received data. Dataanalyzer 2218 may create a data structure for each classification.Additionally, data analyzer 2218 may store the captured informatics andtelematics data in the data repository 310 (which is shown, in FIG. 13 ,as being part of, or used by, insurance server 2012). The datarepository 310 may comprise a database or any other suitable storagecomponent. For example, the suitable storage component may comprise, ormay otherwise make use of, magnetic or optical disks, volatilerandom-access memory, non-volatile random—access memory or any othertype of storage device.

It should be appreciated that in some embodiments data analyzer 2218 maybe integrated with other sub-modules within the data analysis module2210, as well as other modules (not shown in FIG. 13 ), such as a userinterface module, that may comprise or may otherwise make use of theinsurance server 2012. The analysis performed by data analyzer 2218 maybe used to make various types of decisions and/or enable the provisionof certain products/services such as those that can be offered by aninsurance carrier. In an embodiment of the present disclosure, at 2800,data analyzer 2218 may identify one or more insurance related decisionsbased on, for example, its interaction with the user interface module.

One type of decision that may be made is a claims decision. For example,if a claim is made against a homeowner's insurance policy associatedwith dwelling 2200, whether the claim is to be paid (or the amount ofthe claim to be paid) may depend on how dwelling 2200 was damaged ordestroyed. Many homeowner's insurance policies insure against variousnatural perils differently (e.g., some policies cover fire but notearthquake), so if an earthquake strikes and dwelling 2200 is foundcollapsed and burnt, there are at least two possibilities as to how thedwelling 2200 arrived in its current condition: (1) the dwelling 2200collapsed from the earthquake and then its collapsed remains burnt, or(2) the earthquake started a fire that burnt the dwelling 2200, and theburnt dwelling 2200 remains collapsed. If fire is a covered risk andearthquake is not, then it may be relevant to determine whether (1) or(2) is what happened, since (2) would be a covered loss event while (1)would not be a covered loss event. Thus, analysis of data associatedwith the dwelling 2200 received at 2792 may be used to determine how thedwelling 2200 was damaged or destroyed, which may be relevant indetermining whether and/or how to pay a claim.

Another type of decision that may be made based on, for example,telematics data received from telematics devices 2752 (at 2794) is anunderwriting decision. For example, an insurance company may collectdata about a vehicle and one or more drivers associated with the vehicleto determine whether to continue insuring that vehicle, or to set thepremium for insuring the vehicle. In various embodiments, data analyzer2218 may update previously received or stored data to determine whethera risk (e.g., an underwriting risk) associated with providing anautomobile insurance policy has changed. Based on the analysis ofdriver's use of the vehicle (including braking and accelerating amongother examples) data analyzer 2218 may recalculate a coverage amount ora premium of the insurance policy. Data analyzer 2218 may amend theautomobile insurance policy based on the telematics data analysis.

Another type of decision that may be made based on captured informaticssensor data is an alert decision. For example, if assessment ofpolicyholder's health and wellness factors indicates a risk of some typeof disease, which may be a concern for the policyholder's health, dataanalyzer 2218 may issue an alert to the policyholder in order toencourage some kind of remedial action, such as seeing a doctor.

Still another type of decision may involve providing recommendations tomake certain adjustments related to policyholder's work habits, forexample. For instance, based upon certain analysis of policyholder'swork habits, data analyzer 2218 may identify a certain pattern that mayincrease occupational risk of injury. In response, data analyzer 2218may make recommendations with respect to, for instance, improper liftingbehavior that may reduce the identified risks related to policyholder'swork habits.

It should be appreciated that the specific decisions that are discussedabove by no means constitute an exhaustive list. Any type of decisionrelated to one or more insurance related products, such as healthinsurance products, property insurance products, vehicle insuranceproducts, long term disability insurance products, and the like may bemade by data analyzer 2218.

According to an embodiment of the present disclosure, at 2802, dataanalyzer 2218 optionally selectively filters aggregated data based onthe type of decisions need to be made. The main idea behind this aspectof the present disclosure is that data analyzer 2218 may selectivelyfilter out any non-relevant data before sending the data to the one ormore predictive models described below, based on the context of theparticular decision. In an embodiment of the present disclosure, datafiltering feature may be implemented based on filtering rules predefinedby the insurance company.

At 2804, data analyzer 2218 preferably utilizes one or more predictivemodels to rapidly make the one or more decisions identified at 2800.Predictive modeling generally refers to techniques for extractinginformation from data to build a model that can predict an output from agiven input. Predicting an output can include predicting policyholder'sfuture behavior patterns and/or health-related risks, performinganalysis to predict an occurrence of a certain peril, such as earthquakeor hurricane, to name a few examples. Various types of predictive modelscan be used to analyze data and generate predictive outputs. Examples ofpredictive models include, but not limited to, Naive Bayes classifiers,linear and logistic regression techniques, support vector machines,neural networks, memory-based reasoning techniques, and the like.Typically, a predictive model is trained with training data thatincludes input data and output data that mirror the form of input datathat will be entered into the predictive model and the desiredpredictive output, respectively. The amount of training data that may berequired to train a predictive model can be large. It is noted thatdifferent types of predictive models may be used by data analyzer

2212 depending on the type of decision and/or type of capturedinformatics sensor data. Additionally, a particular type of predictivemodel can be made to behave differently by data analyzer 2218, forexample, by adjusting the hyper-parameters or via feature induction orselection. In an embodiment of the present disclosure, one or more ofthe predictive models may be a predictive model markup language (PMML)model that defines the application of a model to selectivelyfiltered-out data.

It should be appreciated that some comprehensive insurance relateddecisions may be made by aggregating results provided by the one or morepredictive models. For instance, to recalculate a coverage amount or apremium of the life-insurance policy, data analyzer 2218 may aggregateresults provided by various models that predict risks associated withpolicyholder's health condition, workplace-related risks,dwelling-related risks, CRM tool used by the insurance company,hurricane risk, earthquake risk, flood risk, crime risk, wildfire risk,lightning risk, hail risk, sinkhole risk, unstructured data available,and the like.

At 2806, data analyzer 2218 preferably provides results to users via,for example, the aforementioned user interface module. Alternatively,data analyzer 2218 may store the generated results in the datarepository 310.

Advantageously, data analyzer 2218 provides a powerful insurance relateddecision making engine that is contingent upon dynamically capturedinformatics sensor data. In another aspect, data analyzer 2218 may alsoprovide for “one click” process to facilitate a rapid insurance-relatedaction. This “one click” process can quickly provide the insured a quoteon, for example and not limited to, a homeowner or auto insurancepolicy. An embodiment of this idea would be the insurance companycollects the information about the insured using the ways illustratedabove, and the insured either only has to provide very little or noadditional information about their home or car. This can quicken thequote process. For example, the insurance company can solicit ahomeowners policy to the insured, the insured can see a picture of theirhome on a mobile phone with all the home characteristics alreadyprovided. The insured would only need to select “buy” and they havepurchased their home insurance.

With reference to FIG. 30 , at 2832, data analyzer 2218 preferablycollects data related to a policyholder's dwelling 2200 from sensors2004 placed at various locations in and around the dwelling 2200. In anembodiment of the present disclosure, this step may involve computingdevice 2006 periodically contacting (via network 2000), at prescribedtime intervals, data analyzer component 2218 running on server 2012 tosend accumulated data. In an alternative embodiment, contact between thedwelling computing device 2006 and data analyzer 2218 may be initiatedwhen the data analyzer 2218 contacts the dwelling computing device 2006.Following the initial contact, data analyzer 2218 may receive data fromthe dwelling computing device 2006. It is to be understood data packetscollected from sensors 2004 can be aggregated in dwelling computingdevice 2006 and sent as an aggregated packet to data analyzer 2218 forsubsequent analysis.

At 2834, data analyzer 2218 preferably collects telematics data from thetelematics device(s) 2752 (shown in FIG. 28 ) that are preferablycoupled to one or more policyholder vehicles 2758. As previouslyindicated, the telematics device 2752 may be used to monitor a number ofaspects of the use of the motor vehicles 2758. For example, thetelematics device 2752 monitors the speed at which the vehicle istravelling. The telematics device 2752 may also able to send datarelated to braking habits of the policyholder (or another driveroperating the vehicle 2758) either using the GPS functionality or byusing an accelerometer or having one or more sensors connected to adeceleration detection device, for example. The telematics device 2752may also be configured and operable to detect the distance travelled andif the vehicle 2758 was driven for a long time period without a break.In addition, the times of the day that the vehicle 2758 is being drivencan be captured as night time driving is statistically more dangerousthan day time driving, especially weekend late night driving. Accordingto an embodiment of the present disclosure, based on the data providedby telematics devices 2752, the data analyzer 2218 may be able todetermine when the vehicle 2758 turns without indicating, for example.In any event, the data from the telematics devices 2752 may betransmitted to an insurance server 2012 over a communication network2000. According to embodiments of the present disclosure, data analyzer2218 may be configured and operable to process a large amount oftelematics data received at 2834.

It should be appreciated that in some embodiments steps 2832 and 2834may be combined into a single step. In some embodiments, steps 2832 and2834 may be changed in terms of order. In some embodiments, one or moreadditional steps may be included.

According to an embodiment of the present disclosure, data analyzer 2218may include a parser configured to parse, aggregate and classify thereceived data (at 2836) based on, for example, type of sensor employedto collect a particular subset of the received data. Data analyzer 2218may create a data structure for each classification. Additionally, dataanalyzer 2218 may pre-process and store the captured informatics andtelematics data in the data repository 310 (which is shown, in FIG. 13 ,as being part of, or used by, insurance server 2012). Pre-processing thecaptured data may involve extracting relevant sensor-based informationto enable storage thereof in the data repository 310. The datarepository 310 may comprise a database or any other suitable storagecomponent. For example, the suitable storage component may comprise, ormay otherwise make use of, magnetic or optical disks, volatilerandom-access memory, non-volatile random—access memory or any othertype of storage device.

At 2838, data analyzer 2218 preferably conducts an analysis to determinea maintenance score value corresponding to the dwelling 2200. Forexample, data analyzer 2218 may generate the maintenance score valuebased upon the dwelling age, dwelling type and any repair and/ormaintenance needs. It is noted that repair/maintenance needs mayinclude, but not limited to, immediate repair needs and preventivemaintenance needs. In general, any dwelling condition that affects theresidents' health or safety may be considered by data analyzer 2218 asrequiring an immediate repair. For instance a hole may have beendetected in the roof of dwelling 2200 (via one or more sensors 2004),requiring immediate repair. As another example, an environmental sensormay have detected a gas leak or any contaminant adverse to human health.As an example of preventive maintenance needs, based upon an air flowanalysis, data analyzer 2218 may have detected that damaged framesand/or dividers allow air leaks into dwelling 2200. Thus, data analyzer2218 may consider window replacement as a preventive maintenance factorin calculation of the maintenance score value. The generated maintenancescore may be represented in the form of a numerical value, such as avalue ranging from 0 to 5 for each of the factors, as well as a combined(average or weighted average) aggregate score.

According to an alternative embodiment of the present disclosure, at2838, data analyzer 2218 may generate a maintenance profilecorresponding to the dwelling 2200 based on the received informaticsdata. The maintenance profile may include both immediate repair needsand preventive maintenance needs. For example, the generated maintenanceprofile may indicate that electrical wiring system is so old that itneeds an immediate upgrade. As another example, the maintenance profilemay point out that gas heating boiler has not received its annualservice. In addition, the maintenance profile may include forwardmaintenance plans, for instance, for the next five to seven years,establishing, for example, the date of the next re-painting job, thedate of the next windows replacement job, and the like. Furthermore, thegenerated maintenance profile may include detailed information about allnecessary and planned repairs.

At 2840, data analyzer 2218 preferably conducts an analysis to determinepolicyholder's driving habits based on compiled historical telematicsdata. The policyholder's driving habits can include preferred drivingspeed, preferred driving speed for a particular roadway, preferreddriving speed for a particular speed limit, preferred cruise controlspeed, preferred lane change frequency, preferred headway distance,preferred lane change space, and/or other data. In this step dataanalyzer 2218 may also determine braking habits of the policyholder (oranother driver operating the vehicles 2758). In addition, data analyzer2218 may also evaluate the times of the day that the vehicle 2758 isbeing driven, as night time driving is statistically more dangerous thanday time driving, especially weekend late night driving. According to anembodiment of the present disclosure, based on the data provided bytelematics devices 2752, the data analyzer 2218 may be able to determinewhen the vehicle 2758 turns without indicating, for example. Accordingto yet another embodiment of the present disclosure, at 2840, data:analyzer 2212 may assess other information indicative of vehicleoperation and maintenance including, but not limited to, tire pressure,mileage, tread wear, and vehicle oil change history.

According to an alternative embodiment of the present invention, at2838, data analyzer 2218 may generate a maintenance profilecorresponding to the insured property 2200 based on the receivedinformatics data. The maintenance profile may include both immediaterepair needs and preventive maintenance needs. For example, thegenerated maintenance profile may indicate that electrical wiring systemis so old that it needs an immediate upgrade. As another example, themaintenance profile may point out that gas heating boiler has notreceived its annual service. In addition, the maintenance profile mayinclude forward maintenance plans, for instance, for the next five toseven years, establishing, for example, the date of the next re-paintingjob, the date of the next windows replacement job, and the like.Furthermore, the generated maintenance profile may include detailedinformation about all necessary and planned repairs.

At 2840, data analyzer 2218 preferably conducts an analysis to determinepolicyholder's driving score based on compiled historical telematicsdata. The policyholder's driving habits can include preferred drivingspeed, preferred driving speed for a particular roadway, preferreddriving speed for a particular speed limit, preferred cruise controlspeed, preferred lane change frequency, preferred headway distance,preferred lane change space, and/or other data. In this step dataanalyzer 2218 may also determine braking habits of the policyholder (oranother driver operating the vehicles 408). In addition, data analyzer2218 may also evaluate the times of the day that the vehicle 408 isbeing driven, as night time driving is statistically more dangerous thanday time driving, especially weekend late night driving. According to anembodiment of the present invention, based on the data provided bytelematics devices 402, the data analyzer 2218 may be able to determinewhen the vehicle 408 turns without indicating, for example. According toyet another embodiment of the present invention, at 2840, data analyzer2218 may assess other information indicative of vehicle operation andmaintenance including, but not limited to, tire pressure, mileage,treadwear, and vehicle oil change history.

It should be appreciated that in some embodiments, at 2842, dataanalyzer 2218 may integrate analysis performed at 2838 and 2840 togenerate a policyholder profile corresponding to the policyholderassociated with the dwelling 2200 and vehicle 2758. In some embodiments,the policyholder profile may include material, geographical, and/orbehavioral attributes that may influence the probability that apolicyholder may personally experience or cause an insured loss. Forexample, the policyholder profile may include a policyholder's name,address, phone number, and birth date. Other policyholder profile datamay include policyholder risk attributes and a claim history.Policyholder risk attributes may include data that indicates thepolicyholder, residents, or any individual connected to the policy(e.g., persons residing in, working in, or otherwise using the dwelling2200, persons driving the vehicles 2758 associated with the policy) havean increased or decreased probability to experience a fire or other lossto the insured dwelling 2200 and/or experience any loss to the insuredvehicle 2758. The policyholder risk attributes may include demographic(e.g., marital status, age, etc.), geographic (e.g., urban, suburban,rural, etc.), and behavioral (e.g., poor maintenance score/profile, highrisk driving habits, etc.) attributes of the policyholder or otherresidents/drivers. The claim history may also indicate a type of riskfor the insurer as policyholders with more numerous claims may indicatea higher probability of experiencing a property loss than policyholderswith fewer claims.

It should be appreciated that in some embodiments data analyzer 2218 maybe integrated with other sub-modules within the data analysis module2210, as well as other modules (not shown in FIG. 13 ), such as a userinterface module, that may comprise or may otherwise make use of theinsurance server 2012. The analysis performed by data analyzer 2218(e.g., at 2838-2842) may be used for various insurance underwritingpurposes. For example, the aforementioned insurance underwritingpurposes may include underwriting decisions related to at least one ofhealth insurance products, property insurance products, life insuranceproducts, vehicle insurance products, long term disability insuranceproducts, and the like. In an embodiment of the present disclosure, at2844, data analyzer 2218 may identify one or more insurance underwritingpurposes based on, for example, its interaction with the user interfacemodule and may use the policyholder profile generated at 2842 to makethe corresponding underwriting decision.

One type of underwriting decision that may be made is a claims decision.For example, if a claim is made against a homeowner's insurance policyassociated with dwelling 2200, whether the claim is to be paid (or theamount of the claim to be paid) may depend on how dwelling 2200 wasdamaged or destroyed. Many homeowner's insurance policies insure againstvarious natural perils differently (e.g., some policies cover fire butnot earthquake), so if an earthquake strikes and dwelling 2200 is foundcollapsed and burnt, there are at least two possibilities as to how thedwelling 2200 arrived in its current condition: (1) the dwelling 2200collapsed from the earthquake and then its collapsed remains burnt, or(2) the earthquake started a fire that burnt the dwelling 2200, and theburnt dwelling 2200 remains collapsed. If fire is a covered risk andearthquake is not, then it may be relevant to determine whether (1) or(2) is what happened, since (2) would be a covered loss event while (1)would not be a covered loss event. Thus, analysis of data associatedwith the dwelling 2200 (received at 2832) may be used to determine howthe dwelling 2200 was damaged or destroyed, which may be relevant indetermining whether and/or how to pay a claim.

Another type of decision that may be made based on, for example,telematics data received from telematics devices 2752 (at 2834) is anunderwriting decision related to a vehicle (i.e., vehicle 2758). Forexample, an insurance company may collect data about a vehicle and oneor more drivers associated with the vehicle to determine whether tocontinue insuring that vehicle, or to set the premium for insuring thevehicle. In various embodiments, data analyzer 2218 may dynamicallyupdate previously received or stored data to determine whether a risk(e.g., an underwriting risk) associated with providing an automobileinsurance policy has changed. Based on the analysis of driver's use ofthe vehicle (including risky braking and accelerating habits, amongother examples) data analyzer 2218 may recalculate a coverage amount ora premium of the insurance policy. Data analyzer 2218 may amend theautomobile insurance policy based on other information indicative ofvehicle operation and maintenance and/or dwelling operation andmaintenance.

Another type of decision that may be made based on captured informaticssensor data is a life insurance underwriting decision. For example, dataanalyzer 2218 may facilitate the evaluation of the risk associated witha prospective policyholder (based on the aggregated data included in thepolicyholder's profile) against the insurer's underwriting criteria tocreate the life insurance policies. In an embodiment of the presentdisclosure, for insurance underwriting purposes data analyzer 2218 mayconsider many factors such as dwelling's structural condition,policyholder's lifestyle, risky habits and trends, environmentalconditions related to the dwelling 2200, driving style and otherinformation that may be contained in the policyholder's profile.

Still another type of decision may involve providing recommendationsrelated to a combined homeowner's and vehicle insurance policy, forexample. For instance, data analyzer 2218 may consider all riskparameters associated with homeowner's insurance in combination with oneor more risk parameters related to a vehicle insurance policy based onthe aggregated data contained in the policyholder's profile. Inresponse, data analyzer 2218 may make certain recommendations, such as,but not limited to, a premium discount, with respect to the combinedhomeowner's and vehicle insurance policy.

It should be appreciated that the specific decisions that are discussedabove by no means constitute an exhaustive list. Any type ofunderwriting determination related to one or more insurance relatedproducts, such as health insurance products, property insuranceproducts, vehicle insurance products, long term disability insuranceproducts, and the like may be made by data analyzer 2218 based upon theaggregated informatics and telematics data.

At 2848, data analyzer 2218 preferably provides a notificationindicative of one or more above-described underwriting decisions made bydata analyzer 2218. It is to be appreciated that data analyzer 2218 maybe configured to electronically deliver all notifications regardingcorresponding underwriting determinations. The notification can beanything that advises a policyholder, device, or computer system of theone or more underwriting matters, including but not limited to, adisplay of text on a local display screen, a message in an email sent toa local or remote computer, a text message, a communication to a remotecomputer system. The electronic delivery may include integration ofnotification functionalities. It is to be also understood andappreciated that data analyzer 2218 may be configured and operational tointegrate with policyholder's communicative computing devices (e.g.,smart phones (via an app), computers, tablets, smart TV's, vehiclecommunication systems, kitchen communication systems, etc.) for sendingsuch notifications regarding such suggested insurance policyalterations. In an embodiment of the present disclosure, eachnotification may include, but not limited to, recommended insuranceproducts, adjusted coverage limits and premiums, liability coverageadjustments, and the like.

With reference to the process 2860 of FIG. 31 , at 2862, dwellinganalyzer 2212 preferably collects data from sensors 2004 to determine anumber of people occupying the dwelling 2200 at various points in timefor insurance purposes. In an embodiment of the present disclosure, thisstep may involve computing device 2006 periodically contacting (vianetwork 1 00), at prescribed time intervals, data analyzer component2218 running on server 2012 to send data collected by a plurality ofmotion sensors 2004. It is noted, a variety of motion sensors 2004 arepreferably installed at various points around the dwelling 2200 such asin the living room, bedroom, kitchen, and bathroom. The sensors arearranged to communicate with the computing device 2006, which, forexample, may be located in a hallway near a main entrance of thedwelling 2200. The one or more motion sensors 2004 may be configured andoperational to monitor movement of dwelling inhabitants in differentareas of the dwelling 2200. In an embodiment of the present disclosure,motion sensors 2004 may comprise passive infra-red detectors. Dwellinganalyzer 2212 may determine, for example, whether the dwelling 2200 wasoccupied by more than one inhabitant by detecting substantiallysimultaneous motion patterns at various points around the dwelling 2200.

At 2864, dwelling analyzer 2212 preferably processes the informaticsdata collected by a plurality of motion sensors 2004 to determine dailyrest-activity pattern. For example, dwelling analyzer 2212 may estimaterest-activity parameters such as bed time, rise time, sleep latency, andnap time for one or more inhabitants of the dwelling 2200 by combiningdata from multiple sensors 2004 located around the dwelling 2200. Asanother example, dwelling analyzer 2212 may be configured to determinewhether the dwelling remains unoccupied for an extended period of time.This information may be used by policy analyzer 2216, for instance, todetermine proper insurance coverage levels for personal propertycontained within the dwelling 2200.

At 2866, based on data collected from sensors 2004 regarding a dwelling2200, dwelling analyzer 2212 preferably conducts an analysis todetermine daily cooking activity pattern of one or more dwelling 2200inhabitants. In an embodiment of the present disclosure, one or moreappliance sensors 2004 may be employed to measure the use of cookingappliances such as a kettle, a fridge, a washing machine, a microwaveoven or an electric cooker. For example, dwelling analyzer 2212 maydetect the cooking time trends by detecting that a rice cooker ormicrowave oven is turned on/off, detecting that a gas range or an IH(Induction-Heating) cooking heater is turned on/off or detecting othercooking home electric appliances are turned on/off. As another example,dwelling analyzer 2212 may combine data collected from various types ofsensors, such as motion and appliance sensors 2004, to determine, forinstance, whether any of the cooking appliances remain unattended for anextended period of time, thus increasing the risk of fire. The dailycooking activity tracking may be adaptive. In other words, dwellinganalyzer 2212 preferably gradually adjusts to the dwelling inhabitant'snew activities and/or habits if they change over time. In general,dwelling analyzer 2212 may assess the risk of fires and explosionsarising from various activities of dwelling inhabitants and/or observedevents and use this information to provide targeted specific advice andguidance at dwelling 2200 to reduce the chance of fires and explosionsarising from the activity.

At 2868, dwelling analyzer 2212 conducts an analysis to determine dailywater consumption pattern. For example, based upon analysis of aplumbing system, dwelling analyzer 2212 may have detected long-termstress on pipes and may estimate future plumbing leaks. In order toprevent water leaks, dwelling analyzer 2212 may recommend reducing waterpressure (e.g., by installing a water softener). As another example,dwelling analyzer 2212 may have detected that dwelling 2200 inhabitantstend to leave shower faucets running while answering the phone, thusincreasing the risk of flooding in a bathroom. Dwelling inhabitants'behavior patterns during a storm can also increase the risk of flooding.For example, a combination of washing clothes, taking a shower, andrunning the dishwasher could add water to a system that may already beoverloaded. The water may have nowhere to go but into the basement ofthe dwelling 2200. Thus, dwelling analyzer 2212 may flag certain waterconsumption patterns of dwelling inhabitants as hazardous and use thisinformation to provide targeted specific advice and guidance to reducethe water leaks at dwelling 2200.

Similarly, at 2870, dwelling analyzer 2212 preferably performs ananalysis to determine daily energy consumption pattern. For example,based upon analysis of the dwelling's 2200 electrical system, dwellinganalyzer 2212 may have detected the load pattern and energy amount aredifferent in weekdays and weekends. For instance, during the weekday theminimum load may occur between 2:00 and 6:00 in the morning when most ofdwelling occupants are sleeping and morning peak may be betweenapproximately 7:00 AM and 10:00 AM, while the night peak may occurbetween approximately 7:00 PM and midnight when the dwelling 2200inhabitants are at home, making dinner and using the entertainmentappliances. On weekends there might be a mid-day peak load betweenapproximately 1 O:OO AM and 03:OO PM, while night peak may occur betweenapproximately 07:00 PM and 10:OO PM. In addition, in this step, dwellinganalyzer 2212 may flag certain energy consumption patterns of dwellinginhabitants as hazardous.

Thus, in steps 2862-2870, dwelling analyzer 2212 collects variouscharacteristics indicative of habits and trends of dwelling 2200inhabitants. At 2872, dwelling analyzer 2212 preferably transmits thesecharacteristics to policy analyzer module 2214. In an embodiment of thepresent disclosure dwelling 2200 inhabitants' habits and trendscharacteristics may include, but not limited to, daily water consumptionand energy consumption patterns, daily cooking activity pattern, numberof inhabitants, hazardous activities pattern, and the like. In analternative embodiment, dwelling analyzer 2212 may store these habitsand trends characteristics in insurance server 2012 database. Thereadings of the amount of energy/water used at dwelling 2200 can be usedto analyze and forecast an expected energy/water bill. This can also beused for budgeting and finance management because a history ofenergy/water usage at the dwelling 2200 or certain appliances can bemeasured and displayed to the homeowner or insurance company. Thesereadings and usage can be provided to the homeowner so that he canbudget X amount of money each month for the energy/water bill. Also, thehomeowner or insurer can track energy/water use and determine based uponthe rate of energy consumption that the homeowner is on a pace to usemore or less energy/water use than is budgeted. If the homeowner is onpace to use more energy/water than is budgeted the insurance company canprovide advice and guidance on how the homeowner can reduce energy use.If the homeowner is on pace to use less energy/water than is budgetedthe insurance company can help the homeowner in moving the unspentportion of the budget amount to a savings device like a CD or moneymarket.

FIG. 32 is a flow diagram of operational steps 2890 of the policyanalyzer module of FIG. 13 in accordance with an illustrated embodiment.At 2892, policy analyzer 2216 preferably receives dwelling 2200 habitsand trends information from the dwelling analyzer 2212. In analternative embodiment of the present disclosure, this step may involvethe policy analyzer 2216 retrieving habits and trends information fromthe insurance server's 2012-storage component. Next, policy analyzer2216 preferably maps the received/retrieved data to a particularinsurance policy associated with the dwelling 2200.

At 2894, policy analyzer 2216 preferably analyzes the insurance policyassociated with the dwelling 2200. For example, policy analyzer 2216 mayidentify the type of the insurance policy. In other words, policyanalyzer 2216 may determine whether the corresponding policy compriseshomeowner's insurance, renter's insurance, umbrella liability insurance,and the like. In addition, policy analyzer 2216 preferably determineswhether the insurance policy covers damage to or destruction of thedwelling 2200, whether it covers damage to or destruction of detachedstructures and whether it covers a plurality of appliances in thedwelling 2200 amongst other coverages.

According to an embodiment of the present disclosure, at 2896, policyanalyzer 2216 checks whether the identified insurance policy type isrenter's insurance. Such insurance typically covers personal propertywithin a dwelling and policy holders typically do not own the structurethey occupy. This type of policy can also cover liabilities arising fromaccidents and intentional injuries for guests of a covered dwelling. Inresponse to determining that dwelling 2200 is covered by the renter'sinsurance policy (step 2896, yes branch), at 2898, policy analyzer 2216may determine additional coverage details associated with this type ofpolicy. For instance, policy analyzer 2216 may identify personalproperty within the dwelling 2200 that is covered by the insurancepolicy. Such property may include, but not limited to, jewelry,furniture, musical instruments, electrical and/or kitchen appliances,guns, furs, various items of fine art and antiques, collectible items,valuable papers, business property, and the like. This step may alsoinvolve policy analyzer 2216 determining property coverage limits aswell as estimating the cost to replace the policyholder's personalbelongings. While steps 2896 and 2898 are discussed with reference torenter's insurance policy, it is understood that this discussion isprovided for illustrative purposes only. A person skilled in therelevant art will recognize that policy analyzer 2216 may determineother types of information relevant to the specific type of theinsurance policy without departing from the scope and spirit of thepresently disclosed techniques.

In response to determining that dwelling 2200 is covered by other typeof insurance policy (step 2896, no branch), policy analyzer 2216, at2900, preferably determines change recommendations to insuranceproducts/services (that may be either currently existing ornon-existing) which may be beneficial to a policy holder in view ofcurrent subscribed insurance products and coverage levels (i.e., currentpolicy coverage levels). Policy analyzer 2216 preferably makes suchdetermination based on data collected by the dwelling analyzer 2212 andbased on analysis conducted at 2894. For instance, if policy analyzer2216 determined that a policy holder (i.e., homeowner or renter) may nothave insurance covering a particular type of event/loss, and based uponcollected and analyzed data from sensors 2004 (amongst possible otherfactors), dwelling analyzer 2214 may provide a recommendation to apolicyholder to subscribe to insurance covering such a particular typeof event/loss. Additionally, policy analyzer 2216 may provide arecommendation to increase, decrease, or make other adjustments topersonal liability limits based upon detected trends and habitsdetermined by the dwelling analyzer 2212 at least in part by datacollected from certain sensors 2004. In an embodiment of the presentdisclosure, such recommendation may relate to any damage associated withthe dwelling 2200. As another example, one or more suggestedmodifications may relate to a loss of one or more of the personalproperty items associated with the dwelling 2200.

At 2902, policy analyzer 2216 preferably provides a notificationindicating suggested insurance coverage modifications. It is to beappreciated that policy analyzer 2216 may be configured toelectronically deliver all notifications regarding suggested insuranceproducts modifications based on detected habits and trends of thedwelling 2200 inhabitants. The notification can be anything thatsecurely advises a policy holder, device, or computer system of thesuggested changes, including but not limited to, a display of text on alocal display screen, a message in an email sent to a local or remotecomputer, a text message, a communication to a remote computer system.It is to be also understood and appreciated that policy analyzer 2216may be configured and operational to integrate with policy holder'scommunicative computing devices (e.g., smart phones (via an app),computers, tablets, smart TV's, vehicle communication systems, etc.) forsending such notifications regarding such suggested insurancemodifications. In an embodiment of the present disclosure, eachnotification may include, but not limited to, detected habits and trendsas well as suggested recommendations with respect to insuranceproducts/services associated with the dwelling 2200.

With reference now to system 2920 of FIG. 33 , shown is insurance server2012 coupled to computing device 2006 for receiving data from sensors2004 preferably relating to a dwelling 2200 in accordance with the abovedescription. In addition to being coupled to dwelling computing device2006, insurance server 2012 is also shown coupled to various image datasources 2922, external computing devices/servers 2760 and an insurancecompany's Customer Relationship Management (CRM) tool/module 2924.Network 2000, and links 109 thereof (FIG. 11 ), preferably couple server2012 to each of the aforementioned components (e.g., computing device2006, CRM module 2924, image data sources 2922 and external computingdevices 2760).

With respect to image data sources 2922, they are preferably operativelycoupled to one or more instruments for receiving image data/information2928 associated with the dwelling 2200. Modern techniques for locatingone or more positions relative to objects of interest typically involveinstruments that are used for surveying, geographical informationsystems data collection, or geospatial data collection. For example,Global Navigation Satellite System (GNSS) receivers are often used inconjunction with the surveying and geospatial instruments in order tospeed position determination. Digital cameras 2926, video cameras 2926,multimedia devices, etc. may also be used for surveying purposes. Theconfluence of these systems/devices produces a variety of image data2928 that may be contained in one or more image data sources 2922, suchas an image-based geo-referencing system, an image database, an imagedatabase management system, among others.

According to an embodiment of the present disclosure, the image datasources 2922 may contain various views of the dwelling 2200. There aretwo principal kinds of “views” described herein: elevation view andaerial view. Elevation view in its strict definition means anorthographic rectified representation of a structure, such as dwelling2200, usually as viewed from ground level. Camera images/photographs notyet rectified for orthographic presentation and not strictly elevationviews, but instead are referred to herein as ‘facade views.’ Aerialviews are images taken from above the objects of interest (i.e.,dwelling 2200), often from airplanes 2923, drones 2925 or satellites2921, and themselves may be rectified or otherwise rendered to becomeorthographic. However, many image databases show them without suchrectification, thus often showing the elevation/facades of buildings ina foreshortened view. It is appreciated that a plan view such as from ablueprint or engineering drawing also falls into the category of aerialviews as described herein. It is to be understood and appreciated, oneor more image data sources 2922 provide image data related to the user'sdwelling 2200 to be aggregated by insurance server 2012 as discussedfurther below.

With regards to external computing devices 2760, each is preferablyassociated with a service provider relating to a user's dwelling. Forinstance, they may include (but are not limited to) emergency responders(e.g., police, fire, medical, alarm monitoring services, etc.), utilitycompanies (e.g., power, cable (phone, internet, television), water),service providers (e.g., home appliance providers), information/newsproviders (e.g., weather reports and other news items) and other likeservice/information/data providers.

With continuing reference to FIG. 33 , in an illustrated embodiment, aninsurance company's CRM module 2924, coupled to insurance server 2012,may be operative to enable the insurance company to understand apolicyholder better. For instance, the CRM tool 2924 may be operative todetermine if the policyholder has a homeowner's policy, a checkingaccount, a life insurance policy and an investment device. If thispolicyholder has multiple lines of business with the insurance company,the data analysis module 2210 may determine the loss performance to belower than another policyholder with a homeowner's policy only.Additionally, the CRM module 2924 may be operative to determine thepayment history for the policyholder. This information may be used todetermine the policyholder's payment history as a data layer for makingrating, acceptability, and/or coverage decisions, among others.

FIG. 34 shows, in the form of a flow chart, exemplary operational steps2950 of the policy manager 2212. Before turning to descriptions of FIG.34 , it is noted that the flow diagram shown therein is described, byway of example, with reference to components shown in FIGS. 11-13 and 35, although these operational steps may be carried out in any system andare not limited to the scenario shown in the aforementioned figures.Additionally, the flow diagram in FIG. 34 shows examples in whichoperational steps are carried out in a particular order, as indicated bythe lines connecting the blocks, but the various steps shown in thesediagrams can be performed in any order, or in any combination orsub-combination.

Generally, property insurance is associated with complex rating,underwriting and insurance-to-value processes, which typically requiresubstantial data gathering activities. Typically, most of such datagathering is accomplished through a series of questions that are oftenanswered by the customer. This manual process can be confusing and timeconsuming resulting in poor customer experience. Advantageously, policymanager 2212 described herein may be configured to facilitate automateddata gathering/aggregation from multiple sources, including image datasources 2922, to streamline the end-to-end process (from quote to claim)of insuring customers. According to various embodiments of the presentdisclosure, in addition to data gathering and aggregation, policymanager 2212 is preferably configured to facilitate a variety ofproperty insurance related processes based upon the aggregated data.These processes include, but are not limited to, underwriting, rebuildcost estimation, providing a quote for an insurance policy, issuance andrenewal of an insurance policy, validation of an insurance claim, andthe like.

With reference to FIG. 34 , at 2952, policy manager 2212 preferablystarts a comprehensive data gathering related to a policyholder'sdwelling 2200 by requesting a policyholder to provide dwelling'slocation information. In an embodiment of the present disclosure, one ofthe service representatives associated with the insurance company andhaving access to the data analysis module 2210 may confer with thepolicyholder regarding property's address or geolocation. Such aconference may be via an Internet chat session or a telephone, forexample. Once, the data analysis module 2210 obtains dwelling's addressor geolocation it may pass the information to policy manager 2212 via acorresponding message. In another embodiment of the present disclosure,policy manager 2212 may receive the geolocation associated with thedwelling 2200 from a positional sensor attached to the dwelling 2200.For example, the positional sensor may be, or may comprise, a GlobalPositioning System (GPS) receiver, which may allow the position ofdwelling 2200 to be determined. It should be appreciated that in someembodiments policy manager 2212 may be integrated with other sub-moduleswithin the data analysis module 2210, as well as other modules (notshown in FIG. 13 ), such as a user interface module, that may compriseor may otherwise make use of the insurance server 2012. Accordingly, thepolicyholder may interact with the policy manager 2212 via such userinterface module or via a website hosted by or otherwise maintained bythe insurance company.

At 2954, in response to acquiring the geographical location of thedwelling 2200, policy manager 2212 may search the one or more image datasources 2922 using a query that includes data specifying a providedgeographic location. If a desired image data or image information 2928does not exist in any of the image data sources 2922, policy manager2212 may send an image capture request to one or more surveyinginstruments, such as satellite 2921, camera 2926, etc., to obtain a newimage of the dwelling 2200. It is noted that according to an embodimentof the present disclosure one or more views of the dwelling 2200 may becaptured in real time. The captured views may include, but are notlimited to, elevation view, aerial view and façade view of the dwelling2200.

According to an embodiment of the present disclosure, if thepolicyholder interacts with the insurance company representative orwebsite via a smart phone 2008 or other portable device, at 2956, policymanager 2212 may transmit the retrieved or captured image of thedwelling 2200 to policyholder's device for dwelling identificationpurposes. Cell phones, smart phones 2008 and related portable devicestypically include a display and a keypad. As shown in the graphical userinterface presented by electronic device 3020 of FIG. 35 , an image 3022showing a façade view of the dwelling 2200 may be presented to thepolicyholder on the smart phone's 2008 display, for example. Accordingto another embodiment, policy manager 2212 may send the image 3022 tothe policyholder via email, for example. By obtaining policyholder'sconfirmation that displayed image 3022 corresponds to the policyholder'sdwelling 2200, policy manager 2212 may proceed with steps 2958-3004 asdescribed below. If at 2954 in addition to acquiring a façade viewpolicy manager 2212 also received one or more aerial views, such asexemplary satellite image 3042 shown in graphical user interfacepresentation 3040 of FIG. 36A, policy manager 2212 may be configured toprocess the satellite image 3042, which may include a view of dwelling'sroof 3044. For example, the policy manger 2212 may generate a plan view3046 of the roof 3044, as shown in FIG. 36B. Thus, according to variousembodiments of the present disclosure, the time-consuming and errorprone data gathering process can advantageously be reduced to requestinggeolocation information related to the dwelling 2200 from thepolicyholder, retrieving the corresponding image from one or more imagedata sources 2922 and receiving policyholder's confirmation. It is notedthat while the above description is directed to a case in which policymanager 2212 utilizes a dwelling image 3022 for property identificationpurposes, the present disclosure is not so limited and other means ofproperty identification are contemplated by various embodiments.

Another embodiment at 2954 includes taking the aerial imagery fromimages 2928 and using the imagery for gathering useful insuranceinformation about the dwelling 2200. For example, and for explanatorypurpose only, the airplane 2925 can take high resolution photos of thedwelling 2200. Algorithms can render those images into 3D models of thehome, use object recognition software to identify exterior construction,roof type, number of windows, and other features of the home. Thesefeatures can be pulled into a tool that will identify the amount ofinsurance needed on the home.

Another embodiment is that risk characteristics can also be identifiedby the images collected. For example, the images 2928 can identify thatdwelling 2200 has a tree touching the roof of the home. When a treetouches the roof it can cause the roof to wear out quicker. An alert canbe sent to the insurance company, the insured, or a 3rd party if a risklike this is identified. Risk characteristics like this can be used forunderwriting, pricing, and acceptability of the homeowner policy.

With reference back to FIG. 34 , at 2958, policy manager 2212 preferablyidentifies one or more insurance related processes to be performed viafurther interaction with the policyholder. For example, this step mayinvolve a determination whether the policyholder is interested inrenewing an existing policy, getting a new policy or just obtaining aquote for a new insurance policy covering dwelling 2200. Oncedetermined, policy manager 2212 may proceed to step 3000.

At 3000, policy manager 2212 may collect various data related to thedwelling 2200 and/or policyholder. As a non-limiting example, the CRMtool 2924 operatively interconnected with policy manager 2212 may beoperative to provide additional information about the policyholder. Forinstance, the CRM tool 2924 may be operative to determine whether thepolicyholder has a homeowner's policy, a checking account, a lifeinsurance policy and an investment device. If the policyholder hasmultiple lines of business with the insurance company, it may bedetermined that the loss performance may be lower than anotherpolicyholder with a homeowners policy only. Additionally, the CRM may beoperative to determine the payment history for the policyholder. Thisinformation may be used to determine the policyholder's payment historyas a data layer for making rating, acceptability, and/or coveragedecisions.

With continuing reference to the aggregating of data in step 3000, in anembodiment of the present disclosure, policy manager 2212 preferablycollects data related to a policyholder's surrounding riskcharacteristics. These risk characteristics can be data layers about thepolicyholder's risk in the area the policyholder lives. Examples of therisks that can be known or determined about the dwelling 2200 include,but are not limited to, the hurricane risk, earthquake risk, flood risk,crime risk, wildfire risk, lightning risk, hail risk, and sinkhole risk.Various information related to these risk factors can be captured by aplurality of sensors 2004 described above with reference to FIG. 13 .This sensor captured data can add to the information known about thepolicyholder and the dwelling 2200 and can be useful to policy manager2212 for determining pricing, acceptability, underwriting, and policyrenewal, among other property insurance related decisions.

Additionally, policy manager 2212 preferably collects data related tounstructured data. Unstructured data (also called unstructuredinformation) refers to data with no uniform structure. Unlike structureddata, which is described by explicit semantic data models, unstructureddata lacks such explicit semantic structure necessary for computerizedinterpretation. According to an embodiment of the present disclosure,policy manager 2212 could collect unstructured data from socialnetworks, such as Facebook and Twitter. For instance, based on thegeolocation information obtained at 2952, policy manager 2212 maydetermine that the dwelling 2200 is situated in a wildfire prone area.Furthermore, a community in this high wildfire area may organizewildfire prevention and mitigation efforts by means of social mediacoordination. The policy manager 2212 and/or other modules hosted by theinsurance server 2012 can monitor the social media sites and may knowthat this community is organizing and utilizing wildfire loss mitigationtechniques. This data could be used by policy manager 2212 along withthe other aggregated information about the policyholder and/or thedwelling 2200 to make various types of decisions and/or enable theprovision of certain products/services such as those that can be offeredby an insurance carrier. Also, policy manager 2212 may determine thatthe aforesaid wildfire community is not giving out the latest wildfirescience information to the community members. Accordingly, policymanager 2212 may provide to the policyholder the latest informationrelated to wildfire science mitigation techniques.

It should be appreciated that policy manager 2212 may store the capturedinformatics data and retrieved image data in the data repository 310(which is shown, in FIG. 13 , as being part of, or used by, insuranceserver 2012). The data repository 310 may comprise a database or anyother suitable storage component. For example, the suitable storagecomponent may comprise, or may otherwise make use of, magnetic oroptical disks, volatile random-access memory, non-volatile random—accessmemory or any other type of storage device.

With continuing reference to the step 3000, in an embodiment of thepresent disclosure, policy manager 2212 optionally selectively filtersaggregated data based on the type of processes need to be performedand/or based on type of decisions need to be made. The main idea behindthis aspect of the present disclosure is that policy manager 2212 mayselectively filter out any non-relevant data before sending the data tomore predictive models described below, based on the context of theparticular decision. In an embodiment of the present disclosure, datafiltering feature may be implemented based on filtering rules predefinedby the insurance company.

At 3002, policy manager 2212 preferably performs one or more processesidentified at step 2958 using the aggregated data in order to provideservices/products desired by the policyholder. Examples of the servicesfacilitated by policy manager 2212 may include, without limitation,providing a quote for an insurance policy insuring the dwelling 2200,issuing a new insurance policy for the dwelling 2200, renewing thepolicyholder's property insurance policy associated with the dwelling2200, validating an insurance claim associated with the dwelling 2200 ifactual loss occurs, generating an insurance to value (ITV) estimate, andthe like. In addition, prior to providing a quote, issuing and/orrenewing an insurance policy, for example, policy manager 2212 mayconduct a rigorous underwriting process to evaluate risks associatedwith the dwelling 2200. It should be appreciated that policy manager2212 may utilize aggregated data, including image data, to perform theaforesaid processes. For instance, policy manager 2212 may use one ormore images provided by the one or more image data sources 2922 toconduct a virtual inspection of the policyholder's dwelling 2200. Asanother example, if the policyholder is interested in initiating a haildamage claim against his/her insurance policy, policy manager 2212 mayevaluate an image, such as image 3042 shown in FIG. 36A depicting theroof 3044 of the dwelling 2200, to evaluate the extent of the damage,provided that the image 3042 was captured after the date the hail wasreported. As yet another non-limiting example, policy manager 2212 mayutilize image data for insurance renewal purposes. More specifically,prior to issuing a renewed policy, policy manager 2212 may transmit animage capture request to one or more surveying instruments, such assatellite 2921, camera 2926, etc. to obtain a real-time aerial image ofthe dwelling 2200. In addition, policy manager 2212 may retrieve apreviously taken aerial image of the dwelling 2200 that may beassociated, for example, with policyholder's expiring policy. Byanalyzing and comparing these two images policy manager 2212 may becapable of determining any structural changes, structural damage, etc.related to the dwelling 2200. It should be appreciated that the specificexamples of image data utilization that are discussed above by no meansconstitute an exhaustive list.

With continuing reference to the step 3002, policy manager 2212preferably utilizes one or more predictive models to rapidly perform oneor more insurance related process and/or to provide insurance relatedservices identified at 2958. Predictive modeling generally refers totechniques for extracting information from data to build a model thatcan predict an output from a given input. Predicting an output caninclude performing analysis to predict an occurrence of a certain peril,such as earthquake or hurricane, to name a few examples. Various typesof predictive models can be used to analyze data and generate predictiveoutputs. Examples of predictive models include, but not limited to,Naive Bayes classifiers, linear and logistic regression techniques,support vector machines, neural networks, memory-based reasoningtechniques, and the like. Typically, a predictive model is trained withtraining data that includes input data and output data that mirror theform of input data that will be entered into the predictive model andthe desired predictive output, respectively. The amount of training datathat may be required to train a predictive model can be large. It isnoted that different types of predictive models may be used by policymanager 2212 depending on the type of the service/product providedand/or type of captured informatics sensor or image data.

It should be appreciated that some comprehensive insurance relateddecisions may be made by aggregating results provided by the one or morepredictive models. For instance, to recalculate a coverage amount or apremium of the property-insurance policy, policy manager 2212 mayaggregate results provided by various models and available unstructureddata that predict risks associated with hurricane risk, earthquake risk,flood risk, crime risk, wildfire risk, lightning risk, hail risk,sinkhole risk, and the like.

At 3004, policy manager 2212 preferably provides results to users via,for example, the aforementioned user interface module or website.Alternatively, policy manager 2212 may store the generated results inthe data repository 310.

Advantageously, policy manager 2212, fully integrated with other modulesand various data sources described above, provides an improved,efficient and streamlined data gathering process that is contingent upondynamically captured image and informatics sensor data. In anotheraspect, policy manager 2212 may also provide for “one click” process tofacilitate a rapid insurance-related action. This “one click” processcan quickly provide the policyholder a quote on, for example and notlimited to, a homeowner or auto insurance policy. According to anillustrative embodiment of the present disclosure, policy manager 2212preferably aggregates and filters the information about the policyholderand/or a corresponding property using the ways illustrated above, andthe policyholder either only has to provide very little or no additionalinformation about their home or car. This can significantly expedite thequote process. For example, policy manager 2212 can solicit a homeownerspolicy to the policyholder, the policyholder can see a picture of theirhome on a mobile phone (such as image 3022 displayed on smart phonedevice 2008 in FIG. 35 ) with all the home characteristics alreadyprovided. The policyholder would only need to select “buy” and they havepurchased their home insurance.

With certain illustrated embodiments described above, it is to beappreciated that various non-limiting embodiments described herein maybe used separately, combined or selectively combined for specificapplications. Further, some of the various features of the abovenon-limiting embodiments may be used without the corresponding use ofother described features. The foregoing description should therefore beconsidered as merely illustrative of the principles, teachings andexemplary embodiments of this disclosure, and not in limitation thereof.

It is to be understood that the above-described arrangements are onlyillustrative of the application of the principles of the illustratedembodiments. Numerous modifications and alternative arrangements may bedevised by those skilled in the art without departing from the scope ofthe illustrated embodiments, and the appended claims are intended tocover such modifications and arrangements.

The invention claimed is:
 1. A system comprising: one or more sensorsconfigured to generate sensor data representative of characteristics ofa property, wherein the one or more sensors comprise a plurality ofmotion sensors; and an analysis server, configured to: receive sensordata, wherein the sensor data comprises motion sensor data comprising anindication of detected movement of people within a range of theplurality of motion sensors; identify a consistent steady state ofactivity patterns with respect to the property, by: aggregating thesensor data from the plurality of motion sensors; and estimatinginhabitant activities comprising at least one of: expected bedtime,expected rise time, expected naptime, and a sleep latency, wherein theinhabitant activities define the consistent steady state of activitypatterns with respect to the property; determine an indication thatindicates whether the property has been used as a habitat using thesensor data, by: identifying activity patterns of the property atparticular times, based upon the motion sensor data; when the activitypatterns include spikes in the movement of people, frenetic changes inthe movement of people, or a combination thereof, which cause theactivity patterns to fall out of the consistent steady state of activitypatterns with respect to the property, determining that the property isnot being used as a habitat; and otherwise, when the activity patternsdo not include spikes in the movement of people, frenetic changes in themovement of people, or both and instead are within the consistent steadystate of activity patterns with respect to the property, determiningthat the property is being used as a habitat; determine one or moresuggested insurance coverage modifications for the property based uponthe indication; and provide an electronic notification indicating theone or more suggested insurance coverage modifications.
 2. The system ofclaim 1, further comprising a computing device configured to: providethe aggregated sensor data to the analysis server as an aggregatedpacket.
 3. The system of claim 2, wherein the computing device isfurther configured to: pre-process the aggregated sensor data, byfiltering the sensor data prior to sending the aggregated sensor data tothe analysis server.
 4. The system of claim 1, wherein the analysisserver is further configured to: determine a second indication whetherappliances of the property have been maintained using the sensor data;and determine the one or more suggested insurance coverage modificationsfor the property based in part upon the second indication.
 5. The systemof claim 1, wherein the one or more sensors comprise a temperaturesensor, and wherein the analysis server is configured to: determine,from the sensor data, one or more temperatures of the property;determine a second indication of whether the property has been climatecontrolled in a prescribed manner based upon the one or moretemperatures of the property; and determine the one or more suggestedinsurance coverage modifications for the property based in part upon thesecond indication.
 6. The system of claim 1, wherein the analysis serveris further configured to: modify a maintenance score based upon whetherthe property has been used as a habitat.
 7. The system of claim 1,wherein the analysis server is further configured to: determine whetherthe property has been repaired with a prescribed promptness; and updatea maintenance score based upon whether the property has been repairedwith the prescribed promptness.
 8. A tangible, non-transitory,machine-readable medium, comprising machine-readable instructions, thatwhen executed by one or more processors, cause a machine to: receivesensor data generated from a plurality of motion sensors configured togenerate the sensor data, wherein the sensor data is representative ofcharacteristics of a property, wherein the sensor data comprises motionsensor data comprising an indication of detected movement of peoplewithin the range of the plurality of motion sensors; identify aconsistent steady state of activity patterns with respect to theproperty, by: aggregating the sensor data from the plurality of motionsensors; and estimating inhabitant activities comprising at least oneof: expected bedtime, expected rise time, expected naptime, and a sleeplatency, wherein the inhabitant activities define the consistent steadystate of activity patterns with respect to the property; determine anindication that indicates whether the property has been used as ahabitat using the sensor data, by: identifying activity patterns of theproperty at particular times, based upon the motion sensor data; whenthe activity patterns include spikes in the movement of people, freneticchanges in the movement of people, or a combination thereof, which causethe activity patterns to fall out of the consistent steady state ofactivity patterns with respect to the property, determining that theproperty is not being used as a habitat; and otherwise, when theactivity patterns do not include spikes in the movement of people,frenetic changes in the movement of people, or both and instead arewithin the consistent steady state of activity patterns with respect tothe property, determining that the property is being used as a habitat;determine one or more suggested insurance coverage modifications for theproperty based upon the indication; and provide an electronicnotification indicating the one or more suggested insurance coveragemodifications.
 9. The machine-readable medium of claim 8, comprisingmachine-readable instructions that when executed by the one or moreprocessors, cause the machine to: determine one or more temperatures ofthe property from the sensor data, wherein the sensor data furthercomprises temperature sensor data; determine a second indication ofwhether the property has been climate controlled in a prescribed mannerbased upon the one or more temperatures of the property; and determinethe one or more suggested insurance coverage modifications for theproperty based in part upon the second indication.
 10. Themachine-readable medium of claim 8, comprising machine-readableinstructions that, when executed by the one or more processors, causethe machine to: determine a second indication of whether appliances ofthe property have been maintained using the sensor data; and determinethe one or more suggested insurance coverage modifications for theproperty based in part upon the second indication.
 11. Themachine-readable medium of claim 8, comprising machine-readableinstructions that, when executed by the one or more processors, causethe machine to: receive the sensor data in an aggregated form, asaggregated sensor data packets.
 12. The machine-readable medium of claim11, wherein the aggregated sensor data packets comprise pre-processedaggregated sensor data from a plurality of sensors, filtered using apredetermined condition.
 13. The machine-readable medium of claim 8,comprising machine-readable instructions that, when executed by the oneor more processors, cause the machine to: determine whether the propertyhas been repaired with a prescribed promptness; and update a maintenancescore based upon whether the property has been repaired with theprescribed promptness.
 14. A computer-implemented method, comprising:receiving sensor data generated from a plurality of motion sensorsconfigured to generate the sensor data, wherein the sensor data isrepresentative of characteristics of a property and comprises anindication of detected movement of people within the range of theplurality of motion sensors; identifying a consistent steady state ofactivity patterns with respect to the property, by: aggregating thesensor data from the plurality of motion sensors; and estimatinginhabitant activities comprising at least one of: expected bedtime,expected rise time, expected naptime, and a sleep latency, wherein theinhabitant activities define the consistent steady state of activitypatterns with respect to the property; determining an indication thatindicates whether the property has been used as a habitat using thesensor data, by: identifying activity patterns of the property atparticular times, based upon the sensor data; when the activity patternsinclude spikes in the movement of people, frenetic changes in themovement of people, or a combination thereof, which cause the activitypatterns to fall out of the consistent steady state of activity patternswith respect to the property, determining that the property is not beingused as a habitat; and otherwise, when the activity patterns do notinclude spikes in the movement of people, frenetic changes in themovement of people, or both and instead are within the consistent steadystate of activity patterns with respect to the property, determiningthat the property is being used as a habitat; determining one or moresuggested insurance coverage modifications for the property based uponthe indication; and providing an electronic notification indicating theone or more suggested insurance coverage modifications.
 15. Thecomputer-implemented method of claim 14, comprising: determining one ormore temperatures of the property from the sensor data, wherein thesensor data comprises temperature sensor data; determining a secondindication of whether the property has been climate controlled in aprescribed manner based upon the one or more temperatures of theproperty; and determining the one or more suggested insurance coveragemodifications for the property based in part upon the second indication.16. The computer-implemented method of claim 14, comprising: determininga second indication of whether appliances of the property have beenmaintained using the sensor data; and determining the one or moresuggested insurance coverage modifications for the property based inpart upon the second indication.
 17. The computer-implemented method ofclaim 14, comprising: receiving the sensor data in an aggregated form,as aggregated sensor data packets.
 18. The computer-implemented methodof claim 17, wherein the aggregated sensor data packets comprisepre-processed aggregated sensor data from a plurality of sensors,filtered using a predetermined condition.